Dear Dr. Norvig,

Recently I read AIMA and I'm sending a list of the errors I found
I hope it helps

Raicho


1.Chapter 14, page 515, figure 14.14


	 replace

	 x,w <- Weighted-Sample(bn)

	 with
	 x,w <- Weighted-Sample(bn,e)

2. chapter 14, page 527, line 10

	 replace

	 T(Tall(Nate) /\ T(Heavy(Nate)) = 0.4

	 with

	 T(Tall(Nate) /\ Heavy(Nate)) = 0.4
3.chapter 15, page 545

	 replace


	 bk+1:t = BACKWARD(bk+2:t,ek+1:t)


	 with
	 bk+1:t = BACKWARD(bk+2:t,ek+1)
4.Appendix A, page 982

	 The typo is in the formula for F(x)
	 We can't integrate over variable x because x is the upper
boundary for the integral

5.chaprer 16 page 596

	 replace

	 U(x1,...,xn) = f[f1(x1),...,fn(xn) , ]

	 with

	 U(x1,...,xn) = f[f1(x1),...,fn(xn)] ,

6.Chapter 17 page 637, figure 17.11

	 The utility expectation for player O when E has a mixed
strategy should be -3*p + 4*(1-p) instead of 3*p + 4*(1-p)
	 In the second case the utility expectation for E when O has a
mixed strategy should be -3*q + 4*(1-q) instead of 3*q

+ 4*(1-q)

7.Chapter 18 page 669, line 5 from the bottom
	 replace

	 "Thus, the probability that it agrees with a given example is
at least"

	 with
	 "Thus, the probability that it agrees with a given example is
at most"

8.Chapter 23 page 837, figure 23.1

	 return sequence,best[i]

	 should be replaced with

	 return sequence,best[n]

	 because the overal sequence probability is accumulated in best
[n]

9.Chapter 24 page 869

	 In the formula of the Gaussian filter sigma ^ 2 should be
replaced with sigma or it should be placed under the square

root

On Thu, 25 Mar 2004, Famofo Julius Seun wrote:

>
> Hi, i am about to start my final year project in AI.
>
> Any ideas, suggestions?
>
Yes.  You could work on implementing an artificial intelligence
based on the following theory-based Cognitive Architecture for AI:

http://freshmeat.net/projects/ai/#comment-30449 == AI has been solved.

Alife Main Artificial Intelligence Program Loop (or Ringlet of Modules)
--- enBoot (English Bootstrap)
--- Security
--- --- HCI (Human-Computer Interaction)
--- --- Rejuvenate (for cyborg immortality)
--- --- psiDecay
--- --- Ego
--- Sensorium
--- --- Audition
--- --- --- Listen
--- --- --- --- audSTM (auditory Short Term Memory)
--- --- --- --- --- audRecog (auditory Recognition)
--- --- --- oldConcept
--- --- --- --- Parser
--- --- --- --- --- Instantiate
--- --- --- --- Activate
--- --- --- --- --- spreadAct (spreading Activation)
--- --- --- newConcept (machine learning)
--- --- --- --- enVocab (English Vocabulary)
--- --- --- --- Parser
--- --- --- --- --- Instantiate
--- Emotion
--- Think
--- --- Activate
--- --- --- spreadAct (spreading Activation)
--- --- English
--- --- --- Ask
--- --- --- --- wtAuxSDo (what+Auxiliary+Subject+Do)
--- --- --- --- --- Speech
--- --- --- --- --- --- Reentry
--- --- --- negSVO
--- --- --- --- auxVerb
--- --- --- --- --- Speech
--- --- --- --- --- --- Reentry
--- --- --- SVO (Subject+Verb+Object)
--- --- --- --- nounPhrase
--- --- --- --- --- Reify
--- --- --- --- --- Speech
--- --- --- --- --- --- Reentry
--- --- --- --- --- Activate
--- --- --- --- --- --- spreadAct
--- --- --- --- verbPhrase
--- --- --- --- --- Reify
--- --- --- --- --- Speech
--- --- --- --- --- --- Reentry
--- --- --- --- --- nounPhrase
--- --- --- --- Conjoin
--- --- --- --- --- Speech
--- --- --- --- --- --- Reentry
--- Volition
--- Motorium

A.T. Murray
--
http://mind.sourceforge.net/aisteps.html#aitree -- AI Algorithm Steps
http://doi.acm.org/10.1145/307824.307853 -- ACM Sigplan on Mind.Forth
http://slashdot.org/~Mentifex/journal/68552 - Slashdot news for nerds
http://mentifex.virtualentity.com/theory5.html -- AI4U Theory of Mind

Hello bob,
Do you mean the 3 concept's relationship?
1. environment
2. agent head
3. agent body

My idea are as follows:
1. Every agent contains 2 parts, 1 is "agent head", the other is "agent body".
2. The agent through its body's sensors to get percept from environment. The
percept has been sent to "agent head" for process, and "head" produce out the
"action". The "action" has been sent to "agent body" for execution. "execuation"
will change some aspect of environment.

3. In the sourcecode of "aima-lisp-code\agents\agents\agents.lisp" file, it
contains Mr. Author's design Decision mark.
====quotation start==============
;; We have decided that the agent and its body are two separate objects.
;; We could have combined the agent and its body into one object.  But then
;; each new type of agent would need to inherit from both AGENT and some
;; body type, such as OBJECT.  This would require multiple inheritance,
;; which is part of CLOS, but is not in our simple implementation for those
;; who don't have CLOS.  In any case, it would get messy.  We think that
;; separating agents from agent-bodies is a good thing for this
;; implementation.  (Just don't take it too far and assume that this says
;; anything about the mind-body problem.)
====quotation end================


I hope the above information is useful to you.
Kind regards
chenyu

Hello rahul,
Maybe my reply is too late, you have already solved it.

In the file "aima-lisp-code\logic\test-logic.lisp", it contains some "how to use
kb?" code. I think this code may be useful to you.
Please attention to "ask-pattern".


===========quotation=======================
"A family relationships knowledge base and problem."
   ((tell kb2 '(Mother Gerda Peter)))
   ((tell kb2 '(Father Torsten Peter)))
   ((tell kb2 '(Father Peter Isabella)))
   ((tell kb2 '(Father Peter Juliet)))
   ((tell kb2 '(=> (mother $x $y) (parent $x $y))))
   ((tell kb2 '(=> (father $x $y) (parent $x $y))))
   ((tell kb2 '(=> (and (parent $g $p) (parent $p $c)) (grand-parent $g $c))))
   ((ask-patterns kb2 '(grand-parent $x $y))
    '((Grand-parent Gerda Isabella) (Grand-parent Gerda Juliet)
      (Grand-parent Torsten Isabella) (Grand-parent Torsten Juliet)))

   "Now the 'Criminal' problem from [p 271-272]."
   ((setf kb3 (make-horn-kb)))
   ((tell kb3 "American(x) ^ Weapon(y) ^ Nation(z) ^ Hostile(z) ^ Sells(x,z,y)
		  => Criminal(x)"))
   ((tell kb3 "Owns(Nono,M1)"))
   ((tell kb3 "Missle(M1)"))
   ((tell kb3 "Owns(Nono,x) ^ Missle(x) => Sells(West,Nono,x)"))
   ((tell kb3 "Missle(x) => Weapon(x)"))
   ((tell kb3 "Enemy(x,America) => Hostile(x)"))
   ((tell kb3 "American(West)"))
   ((tell kb3 "Nation(Nono)"))
   ((tell kb3 "Enemy(Nono,America)"))
   ((tell kb3 "Nation(America)"))
   ((ask kb3 "Criminal(West)") 't)
   ((ask-pattern kb3 "Criminal(x)" "x") 'West)

   )
=============quotation end=====================



kind regards
chenyu (shanghai, china).



-----Original Message-----
From: Rahul Kotamaraju [mailto:rahul061278@...]
Sent: 2004Äê3ÔÂ30ÈÕ 5:04
To: aima-talk@yahoogroups.com
Subject: [aima-talk] FOL

hello,

im new here. im not sure if the question im going to pose here has
already been answered.

in the "logic" section of AIMA code, how does ask-each function (w.r.t
FOL.lisp) work?
Lets say ive created an fol-kb.
(setq kb (make-fol-kb))
(tell kb "Classroom(C1)")
(tell kb "Classroom(C2)")
(tell kb "IsBigger(C1,C2)")

1.if i want to query the kb to ask/ask-each if Classroom C1 is bigger
than C2 then how do I do it?
2.the clauses that i have added above to the kb - are they in the
right form?

regards
rahul




Yahoo! Groups Links

Someon please correct me if I wrong, but in my interpretation the actuators as
in conceptualy part of the agent.
But when you make a software implementation on the  pair agent-environment you
have to implement the actuatror, and the sensor for that matter, as methods
of the class environment.
That is so for you to be able to decouple the agent and the environment. In
that way when an agent want to act over an environment it should call the
proper method in the class environment.
This is in fact the best way to do this because doing things this way the
agent doesn't need to know the environment internal structure.

Mauricio


On Monday 19 April 2004 23:25, Bob Riley wrote:
> I am starting on some of the computing exercises in chapter 2 and
> have a question regarding task environment.  According to the book,
> task environment is specified by performance measure, environment,
> actuators, and sensors.  The 1st two of these I can understand - but
> why are acuators and sensors included in the task environment?
> Shouldn't the task environment be the elements of interest outisde
> of the agent?  Aren't sensors and actuators part of the agent
> itself?  Upon first seeing this, I thought that my interpretation of
> agent may be wrong - maybe the agent is simply the program/function
> and the actuators and sensors are external entities that the agent
> interacts with.  But there are several examples in this chapter
> where the actuators and sensors are considered to be part of the
> agent.  Can someone clear this up?  Is it just me or does the book
> seem to be altering the definition of agent in different parts of
> the chapter?
>
> Thanks,
>
> Bob
>

--
Prof. Dr. Maurício Amaral de Almeida
malmeida@...

Hello Noha,
5. KQML - XML (Agent Communication Language)
Because recently, I am researching for VRP problem and decide to use the
multi-agent to solve the problem. Therefore I have found related documents about
ACL and KQML.

1. For ACL, it is defined by FIPA organization. (foundation for intelligent
physical agents).
	 1.1 FIPA website:  www.fipa.org
     1.2 FIPA's documents, such as "SC0061G,SC00037J", are the specification of
ACL.
     1.3 ACL is standard communication language between many agents.

2. For KQML, it is one implementation of ACL by XML method. I just know this.

3. In addition, FIPA-ACL is another implementation of ACL.

4. If you want to try to use multi-agent, you can try to use "jade3.1" software,
written by java, free software.

5. Because the modern business requires flexible production, flexible
management. Under this background, new flexible, high-extensibility system is
required. Multi-agent can satisfy this requirement. This is important reason of
multi-agent development.

I hope the above information is useful to you.

Thank you for your attention.

Kind regards
Chenyu (shanghai, china)

-----Original Message-----
From: Noha Greiss [mailto:ngreiss@...]
Sent: 2004Äê3ÔÂ26ÈÕ 16:39
To: aima-talk@yahoogroups.com
Subject: [aima-talk] Choosing Tool For Experimental Paper

Hello All,

I have to choose from the following tools to do an Experimental
Paper as part of my Advanced AI Course.

Can anyone please help me choosing based on which is the most used
and currenlty recent technology as I am new in this field.

1. Hugins (Distributed Belief Networks)
2. Grass Hopper (Mobile Agents)
3. ILOG (Planner)
4. CBR
5. KQML - XML (Agent Communication Language)
6. Matlab Toolboxes (Neural Networks, Image Processing ...)
7. NETICA - Norsys (Uncertainty Reasoning)

I found some of the commerical sites related to these tools but not
all of them, if you may know the related site for 3,4 or 5 Please
send them to me.

I know that they may tackle different aspects in AI, but the Idea is
that I want the most used and recent topic.. ALso I would appreciate
if you can provide me with some related experimental papers or links
to papers or to good search engines in the related fields.

Thanks a lot and really appreciate your help.
Noha.




Yahoo! Groups Links

If someone has worked out the solution to Exercise 14.4 in AIMA,
I'd appreciate receiving it.

Chuck Dyer
University of Wisconsin - Madison

Ive recently started reading up on AI and was curious to know if
there were any soultions for Chapter one of this book.

Dear sir,

    I'm looking for an excercise about "chain problem" which it had in
chapter 3 (Solving Problems by Searching) of the 1st edition "Artificial
Intelligence, A Modern Approach by Russel& Norvig, 1995". I searched
in my 2nd edition but it has no this excercise.
    Would you please send the "chain problem" (Ex 3.5 or Ex.3.15 I don't
quite sure.) to me via this e-mail ? I need it very much.

Thank you for your kindness

Atorn N.

Hello,
I have asked others to help me to translate it from Japanese
language. But it make me dispointed because it doesn't contain any
information about how to learning. This documents mainly discuss the
software "Mr.Log"'s brief information. This software use "TS (tubu
search)" and "SA(simulated annealing)" to solve the problem.

But after comparing many algorithm (methodology), I have decided to
use multi-agents (trading algorithm) to do my VRP project.
For GUI and data management, to use mapinfo.

If you are interested in VRP and want to make project on it. The
following paper may be useful to you.

1. about mapinfo and VRP
It contains some "machine learning" algorithm, but it doesn't say
details.
==========================
magazine: journal of operational research society
August 2002, Volume 53, Number 8, Pages 842-854
Map-Route: a GIS-based decision support system for intra-city vehicle
routing with time windows
G Ioannou, M N Kritikos and G P Prastacos
Athens University of Economics and Business, Athens, Greece

Correspondence to: G Ioannou, Management Sciences Laboratory,
Graduate Program in Decision Sciences, Department of Management
Science and Technology, Athens University of Economics and Business,
8th Floor, 47A Evelpidon Street and 33 Lefkados Street, Athens 113-
62, Greece. E-mail: ioannou@...

2. multi-agent truck==========================
http://citeseer.ist.psu.edu/455751.html
It shows why multi-agent method is better. It makes the system more
flexible and easy for adding more constraint.


Thank you for your attention.
kind regarsd
chenyu


--- In aima-talk@yahoogroups.com, ³ÂÓí <chenyu468@y...> wrote:
> Hi,
> I have found a introduction which is about VRP as a learning
problem.
> But it is written in Japanease, I can't understand it now. After
> asking helping others for translation, I could reply you later.
>
> The website: http://citeseer.ist.psu.edu/
> contains many paper about VRP. Maybe keyword of "learning VRP" will
> help you found many similars.
>
>
>
> In addition, I found some useful maganizes about this problem. I
have
> found them in my local library (shanghai library). Maybe you could
> find them in your locals too.
> 1. JORS (Journal of the Operation Research)
>    ISSN: 0160-5682
>
> 2. Annals of Operational Research
>    ISSN: 0254-5330
>
> 3. Management Science
>    ISSN: 0025-1909
>
>
> If anyone have any useful reference about it, please let me know.
> Thank you for your attention.
> Best regards/chenyu
>
>
>
> --- In aima-talk@yahoogroups.com, seA <sea12_02@y...> wrote:
> > can i represent this VRP as a Reinforcement Learning problem?
> becaus im thinking about using RL for my mini project,any idea?
> >
> > regards,
> > seA/indonesia
> >
> > ³ÂÓí <chenyu468@y...> wrote:
> > Hi,
> > Yes, ¡®Vehicle route problem¡¯ is a search problem. It is a
central
> > problem in distribution management. The classical problem¡¯s
> > description is:
> > Fact:
> > 1.      brief:
> > a)      One company has many customers for distribution products.
> > The company has many vehicles fore doing the work. Every
customer¡¯
> s
> > order is small. Company wants to design a plan for all vehicles
to
> > lower the distribution cost.
> > 2.      details:
> > a)      G = (V,E) be an undirected graph where V = {v0,v1,?
> amp;shy;vn} is
> > a set of vertices representing customers. E ={(vi,vj)|vi,vj
belong
> to
> > V, i<j} is the edge set.
> > b)      Vertex v0 denotes a depot at which are based m identical
> > vehicles of capacity Q, where m is a decision variable or a
> constant.
> > c)      Each customer of V\{v} has a non-negative demand qi, a
non-
> > negative service time si. (waiting, unloading time)
> > d)      A distance matrix (cij) is defined on E. We use the terms
> > distance and travel time interchangeably.
> > Problem(VRP---for vehicle route problem
> > 1.      designing a set of m vehicles routes having a minimum
total
> > length and such that
> > a)      each route start and ends at the depot
> > b)      each remaining city is visited exactly once by one vehicle
> > c)      the total demand of a route does not exceed
> > d)      The total duration of a route does not exceed a preset
> > limit L.
> >
> > Many people think that the core of VRP is TSP (traveling salesman
> > problem). But it is more difficult than TSP. TSP has only one
> > salesman.
> >
> > Many variants of VRP exists,
> > 1.      To delete the above fact b. Some customer¡¯s order is
very
> > big so that the order is more than the vehicle¡¯s capacity.
> > 2.      Another special vertex appears. It is not customer. It is
> > highway fee collection point. Therefore the Problem-1 requirement
> > should be modified.
> > 3.      Many different kind of vehicle exists, For example, one
> > kind of vehicles are for freezing products, one kind of vehicles
> are
> > for common products.
> > 4.      Every vehicle can have more than 1 route.
> > 5.      etc.
> >
> >
> >
> > There are many different approachs to solve the problem:
> > 1.      hill climbing
> > 2.      simulated annealing
> > 3.      neural network
> > 4.      GA
> > 5.      ant system
> > 6.      etc
> >
> > I think many knowledge of AIMA can be applied to this problem,
and
> > this problem¡¯s requirement is easy to imagine and new
requirement
> > can be added for more difficulty.
> >
> >
> >
> >
> > Thank you for your attention.
> > Best regards/chenyu (shanghai, China)
> >
> >
> >
> > Do you Yahoo!?
> > Yahoo! Mail - More reliable, more storage, less spam

Hello,
I have implemented wumpus problem by prolog by goal-based agent.
I have my original of rules of shooting are not good.
My first version:
1. rule:
if and only if the agent can be sure that the "wumpus" is in front of
him,  He will shoot.
2. result:
The shooting condition is too restrict, that in most time, it is
impossible for agent to collect so much facts to make inference.
3. Because the "arrow(bullet)" quantity is more than 1, I think it is
possible to lower "shooting" condition.


My second version:
1. rule:
If and only if the agent are in the position of "stench" and "wumpus"
doesn't idea, (it means that "wumpus" is near of "wumpus", there is
25% possibility of chance that shooting will kill the "wumpus"), the
agent shooting.

2. result:
The rule seems ok, but in actual implementation, I found the agent
always shooting even the "shooting" fails. I mean "repeated". It
involves in the dead loop.

3. It means that the "shooting" operation should consider "percept",
whether the "wumpus" dies or not. The shooting rule's condition
should be more strict. In addition, the location's "OK(no wumpus and
not pit)" condition should be adjusted. It means "If shooting doesn't
kill the wumpus, it means there is no wumpus" in the position, the
agent can pass it safely (if no pit in the position).

I think even I improve the above "version 2" to "version 3", if there
are many pits in the wumpus world, in many case, the agent can't find
the "gold" and return safely.


Thank you for your attention.
kind regards/chenyu

I think you are right. Because the environment also our program,
rather than a real-world's thing.


kind regards
chenyu



--- In aima-talk@yahoogroups.com, Mauricio Amaral de Almeida
<malmeida@i...> wrote:
> Someon please correct me if I wrong, but in my interpretation the
actuators as
> in conceptualy part of the agent.
> But when you make a software implementation on the  pair agent-
environment you
> have to implement the actuatror, and the sensor for that matter, as
methods
> of the class environment.
> That is so for you to be able to decouple the agent and the
environment. In
> that way when an agent want to act over an environment it should
call the
> proper method in the class environment.
> This is in fact the best way to do this because doing things this
way the
> agent doesn't need to know the environment internal structure.
>
> Mauricio
>
>
> On Monday 19 April 2004 23:25, Bob Riley wrote:
> > I am starting on some of the computing exercises in chapter 2 and
> > have a question regarding task environment.  According to the
book,
> > task environment is specified by performance measure, environment,
> > actuators, and sensors.  The 1st two of these I can understand -
but
> > why are acuators and sensors included in the task environment?
> > Shouldn't the task environment be the elements of interest outisde
> > of the agent?  Aren't sensors and actuators part of the agent
> > itself?  Upon first seeing this, I thought that my interpretation
of
> > agent may be wrong - maybe the agent is simply the
program/function
> > and the actuators and sensors are external entities that the agent
> > interacts with.  But there are several examples in this chapter
> > where the actuators and sensors are considered to be part of the
> > agent.  Can someone clear this up?  Is it just me or does the book
> > seem to be altering the definition of agent in different parts of
> > the chapter?
> >
> > Thanks,
> >
> > Bob
> >
>
> --
> Prof. Dr. Maurício Amaral de Almeida
> malmeida@i...

Hello there,

First of all, congratulations on a great book, Russell and Norvig!

I have two questions that I was hoping you could help me out with:

1. I have a problem with the objective of minimising the makespan; I
have used a reachabilty tree to obtain the different possible results
(which are routes in my case). To get the optimal route, I used a
branch and bound search algorithm and due to the large size of the
problem, I carried out an A* search to the make sure the branch and
bound technique did not explore unnecessary branches in reachabilty
tree. However, I need some other search methods in order to decrease
the number of searches. I was just wondering if there are any other
artificial intelligence search method/techniques that I can use
besides A* to decrease the number of nodes that should be explored in
the reachabilty tree?

2. I have a problem in which the variables change continuously.
currently I am using a reachability tree for analysing this problem
but because the variables change continuously, I do not think a
reachability tree is a good method for analysing this problem. I was
just wondering if someone can introduce me to some other analysing
methods.

I look forward to hearing your replies!!!

Thank you,
Mahsa.

Can anyone tell me where i can find interactive pop quizes
for aima ?

thx
================================================================================\
===========
"Gabung INSTANIA, dapatkan XENIA. Daftar di www.telkomnetinstan.com, langsung
dapat akses Internet Gratis..
Dan ..ikuti "Instan Smile" berhadiah Xenia,Tour S'pore, Komputer,dll, info hub :
TELKOM Jatim 0-800-1-467826 "
================================================================================\
===========

Hi all. I downloaded the lisp sources, and running them under the
demo versions of Corman Lisp and Allegro CL 6.2 both produce errors.
I can load and run them fine using the personal edition of
LispWorks.

Anyone else having similar problems? (I'm running under Win XPPro...)

Cheers,
Bryan

Hi all,

As a part of academic project, I am solving one Cable
Laying problem using GP.

Problem is:
To optimise cost, minimum path of laying cable in area
X to be found.

Inputs are Road, Obstacle (bldg, pond, temple etc),
Delivery points, Source Points.
So, using two dimensional array I represented all
these points like

Path   Path Path
Path   Road Path
Source Road Path
Path   Road Obstcale
Path   Road Path(D)
Path(T)Path Path

T- Turning point (Assumption)
D- Delivery point

Now, to connect with Source to Delivery Point I can
create Turning Points to minimise distance in overall graph.

In my initial population I will have to create minimum
spanning trees of all possible graphs with Turning points.

My problem is:
How can I create graph by connecting edges where
Obstacle is present. Ofcourse, path is available
but lots of turning points may require. So, to walk
and find the path is very messy exercise.

And also how can I evaluate fitness? Because if i take
any formula like Eucilidean etc. then also it will be incorret due to
presence of obstacle between the points.

Pls reply soon.

-bhavin

I find your problem specification somewhat confusing.  I would be
helped by a sample arrray of about 5 x 5  together with a text
describing what the array represents.

It might also be useful to know what resolution is desired.  Some
methods that might be useful for a 100 x 100 array might not work well
due to space or time considerations on a 10,000 x 10,000 array.

Hope I can help.

george

--- In aima-talk@yahoogroups.com, "Bhavin" <bhavin.sanghani@g...> wrote:
> Hi all,
>
> As a part of academic project, I am solving one Cable
> Laying problem using GP.
>
> Problem is:
> To optimise cost, minimum path of laying cable in area
> X to be found.
>
> Inputs are Road, Obstacle (bldg, pond, temple etc),
> Delivery points, Source Points.
> So, using two dimensional array I represented all
> these points like
>
> Path   Path Path
> Path   Road Path
> Source Road Path
> Path   Road Obstcale
> Path   Road Path(D)
> Path(T)Path Path
>
> T- Turning point (Assumption)
> D- Delivery point
>
> Now, to connect with Source to Delivery Point I can
> create Turning Points to minimise distance in overall graph.
>
> In my initial population I will have to create minimum
> spanning trees of all possible graphs with Turning points.
>
> My problem is:
> How can I create graph by connecting edges where
> Obstacle is present. Ofcourse, path is available
> but lots of turning points may require. So, to walk
> and find the path is very messy exercise.
>
> And also how can I evaluate fitness? Because if i take
> any formula like Eucilidean etc. then also it will be incorret due to
> presence of obstacle between the points.
>
> Pls reply soon.
>
> -bhavin

Is this a bug in Chap 23.2 ?

On p. 841, line -7,
"we can rank documents based on the score:
P(r|D,Q)/P(~r|D,Q)=...
"

then on p. 842, line 1,
"With the assumption, we get
P(r|D,Q)/P(~r|D,Q)
=P(Q|D,r)*P(r|D) / P(~r|D)
"

I believe the derivation of the latter has bug.
What I'd suggest, is:
P(r|D,Q)/P(~r|D,Q)
=P(Q|D,r)*P(r|D) / (P(~r|D)*P(Q|D,~r))
=P(Q|D,r)*P(r|D) / (P(~r|D)*P(Q|~r)) by using the assumption on p.
841, last line.

But then the author would need to explain how to calculate the new
term P(Q|~r)).

David Liu

Hi,
I'm looking for the source paper/publication of the equations on the
Language Modeling approach to information retrieval (Chap.23.2,
p.841, P(r|D,Q)=... ).  Does anybody know which paper these
equations came from?

Thanks!
David Liu

Hi-

What license does do the sources in the code repository fall under?  I'm
interested in using some of these on a proprietary contract job.  Can I
use the code directly or do I need to write my own version based on
the repository (or would that be covered by the original license as
well, as is the case with the GPL)?  FWIW, I own the book... ;)  Thanks!

--Peter Fein

--
Peter Fein                 pfein@...                 773-575-0694

Be alert - some terrorists look normal. -Ministry of Information, Brazil

Yahoo! India Matrimony: Find your life partner online.

Should have clarified...  are the *Python* sources in the repository
under the same license as the Lisp sources (located at:
http://www.norvig.com/license.html)?

--Pete

Hi-

What license does do the sources in the code repository fall under?  I'm
interested in using some of these on a proprietary contract job.  Can I
use the code directly or do I need to write my own version based on
the repository (or would that be covered by the original license as
well, as is the case with the GPL)?  FWIW, I own the book... ;)  Thanks!

--Peter Fein

--
Peter Fein                 pfein@...                 773-575-0694

Be alert - some terrorists look normal. -Ministry of Information, Brazil

Hi i got a question here.. im pretty weak with java coding but i
learnt that the best way to solve this question i have is to use
java.

How do i use vectors to create the tree in the first place for this
question? i was thinking if i needed a vector the information needed
would be

Vector CityA (straight line distance) (distance so far=cost)

how do i use the vector to show teh connection or check for
connection for each city?

If anyone can help me with this pls email me.. either with some help
or if u have a suggested solution using java code. I would be most
grateful.. tnx a million.

Rgds
Feroz

---------------------------------------------------------
My aim is to find a path with the shortest distance between any 2
cities in a graph of interconnecting cities.

Input being : a list of city names, their x-coordinate and y-
coordinate. For example

city washington 138.0 145.0

The name of a city is a string of characters without any intervening
spaces.If two cities are connected by a direct route, it is indicated
in the input file. For example,

conn washington boston

indicates that washington is connected by a direct route to boston.
The start city and goal (destination) city is also indicated in the
input file. For example,

start kansas
goal michigan

indicates that kansas is the start city and michigan the goal
(destination) city.

Given the x- and y-coordinates of the cities, the connections between
the cities, the start city and the goal city, the program is to
perform A* search to find a path with the shortest distance from the
start city to the goal city. The straight-line distance is to be used
as the heuristic function, with the assumption that the cities are
laid out on a 2-dimensional plane.

The program must be general and works correctly on any number of
cities and any interconnection configuration.

-------------------------------------
An example inputfile is:
city  washington 138.0 145.0
city  california 149.0 145.0
city  michigan 142.0 137.0
city  boston  145.0 142.0
city  kansas 151.0 146.0
conn  washington boston
conn  washington kansas
conn  california boston
conn  california kansas
conn  michigan boston
start  kansas
goal   michigan

The corresponding outputfile in this case is:
13.067 kansas california boston michigan 0.01 sec

Can u clarify more on your problem?

Disclaimer : I am not an expert at expert systems(no pun intended!).
But i have made some small scale expert systems in traditional
Languages like C/C++ and Java.
--- In aima-talk@yahoogroups.com, Augustine ssevviri <augkaddu@y...>
wrote:
> Hi collegues,
>
> Am here stuck with my MSc proposal.  It is on expert system design
in laboratory medicine.
>
> Iam stuck with the design part in the methodology section.
>
> I get no where for the necessary guidelines. If you could bail me
out.
>
> Please it would be very kind of you.
>
> Hoping to hear from you soon.
>
> Thanks.
>
> Augustine
>
>
> ---------------------------------
> Do you Yahoo!?
> Win 1 of 4,000 free domain names from Yahoo! Enter now.

Vectors will be hardly helpful! I see it nothing more than a
collection of elements just like an array. Moreover its pretty slow.

For your problem there is a much easier implementation,
write a class edge say like,
class Edge
{
/*basic attributes*/
String City1,City2;
float heuristic distance;
/*basic method*/
calcHeuristic()

/*Other methods and attributes may be added as needed*/
}

Then simply create a 2D Matrix
Edge[][];

read from the file and generate the appropriately sized matrix.
u can index the cities as u wish.
for ur example, we can have
0 washington
1 california
2 michigan
3 boston
4 kansas

Notice that all this is done just at the start .. then simply run
your A* algorithm on this matrix(which will have all the heuristic
distances already calculated).

This implementation is much easier to implement and not to mention
smaller.

--- In aima-talk@yahoogroups.com, "wizniz" <wizniz@r...> wrote:
> Hi i got a question here.. im pretty weak with java coding but i
> learnt that the best way to solve this question i have is to use
> java.
>
> How do i use vectors to create the tree in the first place for this
> question? i was thinking if i needed a vector the information
needed
> would be
>
> Vector CityA (straight line distance) (distance so far=cost)
>
> how do i use the vector to show teh connection or check for
> connection for each city?
>
> If anyone can help me with this pls email me.. either with some
help
> or if u have a suggested solution using java code. I would be most
> grateful.. tnx a million.
>
> Rgds
> Feroz
>
> ---------------------------------------------------------
> My aim is to find a path with the shortest distance between any 2
> cities in a graph of interconnecting cities.
>
> Input being : a list of city names, their x-coordinate and y-
> coordinate. For example
>
> city washington 138.0 145.0
>
> The name of a city is a string of characters without any
intervening
> spaces.If two cities are connected by a direct route, it is
indicated
> in the input file. For example,
>
> conn washington boston
>
> indicates that washington is connected by a direct route to boston.
> The start city and goal (destination) city is also indicated in the
> input file. For example,
>
> start kansas
> goal michigan
>
> indicates that kansas is the start city and michigan the goal
> (destination) city.
>
> Given the x- and y-coordinates of the cities, the connections
between
> the cities, the start city and the goal city, the program is to
> perform A* search to find a path with the shortest distance from
the
> start city to the goal city. The straight-line distance is to be
used
> as the heuristic function, with the assumption that the cities are
> laid out on a 2-dimensional plane.
>
> The program must be general and works correctly on any number of
> cities and any interconnection configuration.
>
> -------------------------------------
> An example inputfile is:
> city  washington 138.0 145.0
> city  california 149.0 145.0
> city  michigan 142.0 137.0
> city  boston  145.0 142.0
> city  kansas 151.0 146.0
> conn  washington boston
> conn  washington kansas
> conn  california boston
> conn  california kansas
> conn  michigan boston
> start  kansas
> goal   michigan
>
> The corresponding outputfile in this case is:
> 13.067 kansas california boston michigan 0.01 sec

Augustine ssevviri <augkaddu@...> writes:

> Am here stuck with my MSc proposal.  It is on expert system design in
laboratory medicine.
>
> Iam stuck with the design part in the methodology section.

You may check this book on the classic MYCIN system:

   http://www.aaai.org/Resources/Classics/Mycin/mycin.html


Paolo
--
Why Lisp? http://alu.cliki.net/RtL%20Highlight%20Film

Hello everyone,

the authors state about bidirectional search that (p. 80):

"Bidirectional search is implemented by having one or both of the
searches check each node before it is expanded to see if it is in the
fringe of the other search tree; if so a solution has been found."

Although this is true, if only one search checks in the other's fringe
bidirectional search is complete, but not optimal. Thus in Figure 3.17
p.81, there should be another footnote for bidirectional search
stating that in order to be optimal, both searches have to check the
fringe of the other before they expand each node.

Regards,

Kyriakos Chatzidimitriou