Questions about design and properties of agents that act in a dynamic environment and make decisions towards some goal without user control.

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3
votes
2answers
73 views

About randomness and minmax algorithm with alpha beta pruning

Will choosing the child of a node randomly in the alpha beta algorithm have a better chance to get a cut off than choosing them in order? Here's the pseudocode with my addition marked with ***. ...
2
votes
1answer
23 views

How is the environment designed for testing a reinforcement learning algorithm?

I'm working on a project, and have a candidate algorithm which I'd like to test. Before I go any further, I need to get the hang of how to code the "structure" of the environment in which my system is ...
1
vote
0answers
7 views

Dyna-Q in non-deterministic domains

I've implemented the Dyna-Q reinforcement learning algorithm and it works perfectly on a discrete deterministic environment, the cliff. However, when applying it to a continuous environment (mountain ...
-1
votes
1answer
46 views

Turing tests and humans

How are the questions framed in Turing tests? I mean what factors would one consider before framing questionnaire for the Turing Test.How the questions should be framed to make the test unbiased for a ...
1
vote
0answers
21 views

KDD Machine Learning using K-NN Algorithm Classification Problem

I'm trying to solve a classification problem from the KDD cup archive of 2004. Details can be found here: KDD 2004 Archive I'm only dong the particle physics part. The description of dataset is as ...
2
votes
2answers
43 views

Symmetry in Pattern Databases

I am trying to understand the use of symmetry in pattern databases (Heuristics, single agent search). This is too specialized of a topic to find common videos or explanations in general. I read the ...
0
votes
0answers
10 views

understanding kohonen self organized feature maps

I was learning self organizing feature maps the other day. I want to intuitively understand it because I'm not that good at math. But I still am not very clear about it. I can easily understand ...
1
vote
0answers
28 views

Good language for introduction to self-modifying algorithms? [closed]

So I am trying to find a language with which i can write code to build/search through deductive reasoning 'nets', as well as self-modify it's search algorithms based on information learned from these ...
-1
votes
0answers
24 views

How does the Learning Real Time A-Start work?

I am reading the book Artificial Intelligence: A Modern Approach Stuart Russell, Peter Norvig. It has the following pseudocode for LRTA* algorithm ...
1
vote
1answer
46 views

Expectation Maximization Algorithm for simple naive Bayesian network

I am trying to understand the following network A has two children - B & C (aka common cause) All the variables are binary and can be either 0 or 1. In data values are missing only for some ...
1
vote
2answers
53 views

Skolem constant in existential instantiation for first order logic

For any sentence $\alpha$, variable $v$, and constant symbol $k$ that does NOT appear elsewhere in KB: $$\dfrac{\exists \nu. \alpha}{\mathsf{subst}(\{ \nu / k \},\alpha)}.$$ E.g., $∃x. ...
2
votes
1answer
36 views

Role of computational power in recent AI developments

Today Google's AI won its first game of Go against Lee Sedol, one of the best Go players on the planet. Image interpretation and self-driving cars are other recent success stories in machine learning. ...
0
votes
1answer
65 views

How different is the working of SNN (Spiking Neural Network) as compared to a real Neuron System in biological systems?

Assuming its one step closer to realism as compared to ANN, DNNs and other Neural Network models, what are the primary differences between a real neuron system and SNN?
3
votes
1answer
94 views

What category of AI would a 2048 bot be considered?

I have just delved into the realm of AI and from what I can tell its a very vast field of study. I am a game programmer, so AI in games is particularly interesting to me. My question is, what type of ...
0
votes
1answer
44 views

a program discovering himself how to solve propositional calculus

it is well-known that propositional logic problems such as $$ (p\leftrightarrow q) \lor r \quad\overset{?}{\vdash}\quad (((p\lor q)\to(p\land q)) \land \lnot r)\lor r$$ can be simply solved by ...
1
vote
1answer
74 views

Information about ε-greedy algorithms

I'm working on a paper that uses ε-greedy algorithms for choosing episodes of a sarsa q-learning algorithms. I searched for algorithm but couldn't get so much. Can you please give me the algorithms ...
2
votes
1answer
67 views

Robot lawyer algorithm [closed]

I have a background in physics and have taken some few classes online in Machine learning. But I really do not understand how this Robot lawyer can work: A 19-year-old made a free robot lawyer that ...
1
vote
0answers
14 views

Reasoning approaches for implementing a Knowledge-based System?

What are the major approaches in implementing a Knowledge-based System (KBS)? Approaches used to take decisions in a KBS that I have come across so far are the case-based and rule-based reasoning ...
2
votes
1answer
36 views

What is a good example to illustrate the difference between isomorphic and homomorphic representations?

I am learning about "knowledge representation" in my intro to AI course and one of the key ideas has to do with isomorphic vs homomorphic representations. The examples I find when I google around are ...
4
votes
0answers
31 views

What is the difference between Cased-based Reasoning and Rule-based reasoning?

As stated here, Rule-based Reasoning systems are considered to be "old style" AI that uses rules prepared by humans - as opposed to Neural Networks where machine recognizes pattern i.e. acquires new ...
5
votes
1answer
46 views

Clarification of the definition of a POMDP

From what I understand, a $MDP=(G, A, P, R)$ (markov decision process) is represented as: A complete directed graph $G=(V, E)$ A set of actions $A_u$ for each vertex $u \in V$ A reward function $R$ ...
0
votes
2answers
28 views

What to do when the information gain on decision trees is 0 for all possible splits?

I just started studying decisions trees and I am trying to construct a tree for a training set which uses Status as the class label. I am using the misclassification error as measure of impurity. ...
1
vote
1answer
49 views

Program interpretation for static analysis

Are there any implementations, or even academic work, regarding an application capable of looking at code and inferring what the code actually intends to do? For example, we give it a program that ...
0
votes
0answers
28 views

Belief Propagation in Computer Vision

I am working on dense matching using DSP algorithm. They have used belief propagation to optimize their energy function? How do we do it? I mean how do we assign prior belief? Link: Deformable Spatial ...
4
votes
0answers
51 views

Flaw with Cross Entropy Error in Neural Networks

I've recently been working on creating a neural network to classify handwritten digits. I implemented 1-of-N encoding such that there are the same number of output nodes as possible digits (The ...
2
votes
1answer
58 views

Difference between heuristic-based searching and optimal path searching

I'm currently studying for an AI computer-science course. One thing is difficult for me to grasp and somewhat vaguely explained in my course-material: I understand that with search-methods like e.g. ...
5
votes
1answer
37 views

Explanation of the knowledge representation hypothesis (Brian Smith)

In 1982 Brian Smith proposed his Knowledge Representation Hypothesis: Any mechanically embodied intelligent process will be comprised of structural ingredients that we as external ...
2
votes
1answer
87 views

Can an artificial neural network convert from cartesian coordinates to polar coordinates?

Given cartesian coordinates $x$ and $y$ as input, can a neural network output $r$ and $\theta$, the equivalent polar coordinates? This would seem to require an approximation of the pythagorean ...
0
votes
1answer
73 views

Dynamic Learning (Machine Learning)

I have been given a task to dynamically learn the optimum value of a parameter in a Heuristics Filtering Algorithm used in a tool. The accuracy of the tool increase as the value of K in the ...
1
vote
0answers
32 views

Text data comparison

Okay lets say i have two data structures . two phone data for example containing their Name and spec ( cpu , ram , display etc ) . I want to check if these two phones are the same or not . Their names ...
3
votes
0answers
29 views

what is the best practice for turing test

I'm working on a AI project which generates poems in Turkish language like this project: https://github.com/schollz/poetry-generator It's a successful project but it's a template based poem ...
0
votes
0answers
9 views

Is it possible to retrieve element in a matrix which was trained using Neural Network?

I just studied neural networks and know the basics. Problem: A matrix is trained using neural network (by giving position of an element and the element) One should get the element at (i,j)th position ...
2
votes
0answers
39 views

What are the theoretical and practical contributions of Multiagent Systems to science?

Speaking about multiagent systems (MAS) is about as fuzzy as talking about artificial intelligence systems (AI). They are in essence the distributed counterpart of AI. While there are no so-called ...
0
votes
2answers
77 views

Transforming training data for machine learning algorithms

If you want to make good predictions with machine learning (supervised learning in particular), you need a good training set. And relevant predictors in your feature set can be overshadowed by ...
0
votes
1answer
21 views

Effect of value of k in K-Nearest Neighbor

In K-Nearest Neighbor the value of k decides the accuracy of classification. What are the pros and cons of choosing smaller value for k and larger value for k?
1
vote
1answer
88 views

How do neural networks learn concepts?

I've been learning neural networks and some back propagation stuff, and I heard about google's Tensorflow and how it could learn things like how to carry on conversations. It got me thinking about how ...
1
vote
0answers
18 views

Conceptualising the physical environment in AI and videogame design

This is a bit of a long shot but i'm currently working on a research project in psychology/public health. One of the aims of this project is to develop a typology/"conceptual map" of how things in the ...
1
vote
1answer
25 views

Unification Functions

I need to apply the unification function to unify the following expression: foo(X,X,Y) and foo(Z,p(Z),w) So far, I've determined that I must substitute 'w's for occurances of 'Y', making foo(X,X,w) ...
1
vote
1answer
25 views

Number of states in classical planning

With reference to the Heuristics section of Classical planning in Artificial Intelligence: A Modern Approach by Russell and Norvig, there is a question: consider an air cargo problem with 10 ...
3
votes
0answers
25 views

Limited lookahead pathfinding strategies on infinite graphs

I'm new to pathfinding algorithms and trying to find a good or even optimal heuristic for the following problem: Say you have a 3D square-lattice cuboid graph with randomly removed edges (with ...
6
votes
3answers
92 views

Exploring and interpolating a function using machine-learning?

Which general machine-learning methods are there that try to "learn" or interpolate a smooth multivariate function and which get to actually choose the points at which the function is evaluated during ...
0
votes
0answers
18 views

what is the best theory/model to use for prediction in multivariate data?

I use a software for pollutant propagation on rivers that takes as input a set of parameters (p1, p2, ...pn) and creates an output file which is basically a matrix where on each row there is ...
1
vote
0answers
39 views

Teaching perceptrons colors? [closed]

I am learning about artificial neural networks and I've decided to go with perceptrons. I already made a sample program that can learn based on the learning data, but when I tried to make it recognize ...
1
vote
1answer
193 views

In principle, what is the relation between Artifical Intelligence and Turing machine?

I am working on my cs project about AI & Turing machines, so i know that Artifical Intelligence is meant to implement different algorithms into the machine {the computer} to solve a problem or a ...
5
votes
0answers
487 views

What is Least-Constraining-Value?

In constraint satisfaction problems, heuristics can be used to improve the performance of a bactracking solver. Three commonly given heuristics for simple backtracking solvers are: ...
2
votes
1answer
18 views

Can high-order unification be applied to programming by example?

In 2007, it has been proven that high-order unification is decidable on the pattern matching case. If that is true, what is stopping someone to write an equation like: ...
0
votes
1answer
63 views

Which attributes to consider for credit card fraud detection on an ATM? [closed]

I am working on a project in which I am supposed to come up with a system that detects fraud from a credit card transaction. I read about techniques that others have used and decided to use Artificial ...
1
vote
1answer
88 views

What kind of Neural Network (if any) could fit two sets of data points?

I have two datasets, one of animal migration patterns (collected over the course of a couple years) that consists of many points on an x, y plane (latitude, longitude), and the other of ocean surface ...
1
vote
2answers
55 views

Why does an admissible heuristic mean A* is optimal?

An admissible heuristic never overestimates the cost to reach the goal. However, isn't that only the relative difference between heuristics for two different paths matter? Say we have optimal path A ...
1
vote
1answer
130 views

Table-Driven Agent Program

I have two questions regarding a paragraph about table-driven agent programs from Modern Approach to Artificial Intelligence 3rd Edition. "Let $\mathbb{P}$ be the set of possible percepts and let T ...