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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0answers
18 views

Research work on computational models for a “specific” person's behaviors

Is there active research work on creating computational models of a "specific" person's behaviors (general behaviors, emotions, actions...)? What are some references for such research? I tried google ...
13
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4answers
4k views

Did 'Eugene Goostman' really pass the Turing test?

It is being said that 'Eugene Goostman', a computer programme developed to simulate a 13-year-old boy, managed to convince 33 per cent of the judges that it was human, and thus passed the Turing Test. ...
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0answers
12 views

Previous approaches for encoding physical affordances

From Wikipedia, an affordance is: a relation between an object or an environment and an organism, that affords the opportunity for that organism to perform an action Previously what approaches ...
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1answer
13 views

What is a continuous environment for an agent?

I know the environment of an intelligent agent is divided to discrete and continuous. But I think they are relevant to sensors and actuators of the agent itself. Moreover, environment may have many ...
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2answers
44 views

Which type of computer programs could be called intelligent agents?

I know some computer programs can be modeled as intelligent agents, for example a chess program which plays against a human. The environment is the chess board stored in the memory and actuators are ...
0
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0answers
16 views

Can Ontologies be used for defining tactics and technical features?

The generic use of ontologies is defining terms and relations between them in a specific domain. And in some cases they are used with the cognitive architectures to make intelligent agents for ...
4
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4answers
186 views

What are the practical uses of ontologies?

I have read many papers and books about ontologies and I am trying to figure out that how they are used in a real project? For example how the ontology for a soccer player robot can be defined and ...
3
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0answers
83 views

Who coined the term “artificial intelligence”?

The most obvious (and commonly given) answer to this question is John McCarthy, but I have traced the first usage of this term to a 1955 paper, which McCarthy co-authored with Marvin Minsky, Nathaniel ...
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0answers
43 views

Formulating an arrangement problem with STRIPS

The problem is rearranging furniture in a flat. We are given rectangular rooms of natural width and height with doors between them, (the walls have no width) and rectangular furniture at starting ...
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1answer
65 views

Cognitive Computing vs Artificial Intelligence?

Can anyone please tell me the difference between them? A brief definition of Cognitive Computing would appreciated. Also how does cognitive computing relate to neural networks? Thank you~
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0answers
163 views

What is an example of Licklider’s idea of man-machine symbiosis in constructing information systems?

I am trying to understand Licklider’s idea of man-machine symbiosis in the real world, does anyone know of any real world examples of the use of a man-machine symbiosis? Would it be correct to say ...
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1answer
36 views

Books to get prepared before self studying Artificial Intelligence [closed]

I want to study Artificial Intelligence from Artificial Intelligence: A Modern Approach by Russell and Norvig, in the mid-year vacation. I want to get prepared before diving into the book so I decided ...
1
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1answer
46 views

negative effective branching factor it's possible?

i've implemented A* algorithm in python,after that i calculate with this python function the effective branching factor $ B^* $ $ T+1=1+B^*+(B^*)^2+⋯+(B^*)^L$ where $T$ is the number of expanded ...
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1answer
40 views

Why do heuristic functions only approximate the real value of the cost?

As stated in the title I'm wondering why do heuristic functions only approximate the real value of the cost? I understand it can never overestimate, but can it ensure the cost is accurate?
2
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3answers
65 views

Can someone clarify this unification algorithm?

I've been having trouble understanding a unification algorithm for first order logic, as I don't know what a compound expression is. I googled it, but found nothing relevant. I also don't know what a ...
3
votes
1answer
117 views

Genetic Algorithm, Neural Network, Deep Learning, Machine Learning Similarities and Applications? [closed]

I am a computer engineering student and trying to get the idea behind all these Artificial Intelligence Concepts and applications. I know little theoretically about machine learning and some high ...
2
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2answers
71 views

ANN - Backpropagation with multiple output neurons

Can I utilize the backpropagation algorithm in a layered, feed-forward ANN in instances where there are multiple output neurons? If so, how? Links to (somewhat) comprehensible resources would be ...
0
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1answer
33 views

what is the general name of this problem?

what is the general name of a problems where learning agent observe new data as a learning goes on. For example when playing platformer games one must incrementally learn new level areas and states ...
1
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1answer
39 views

Programs for artificial system design? [closed]

Are there program systems that can discover the need of routines - and then design them, code them and use them as parts of the system? Any group of humans trying to pursue an activity has to ...
1
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0answers
39 views

Formula for number of parameters in an undirected graphical (probability) model

I have googled endlessly, and I cannot find it. Can anyone point me to a reference that gives a way to calculate the number of parameters in an undirected Graphical Model? Adapting from the similar ...
0
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2answers
53 views

Why is And-Or-Graph-Search called a search algorithm?

An algorithm in Artificial Intelligence: A Modern Approach for planning in stochastic, fully observable environments is called And-Or-Graph-Search, implying that it's a search algorithm. However, I ...
3
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0answers
64 views

Prerequisites for AI and machine learning [closed]

I am interested in the field of AI and machine learning and I am fairly good at mathematics and statistics and programming in general. However I lack a formal CS education and my undergraduate degree ...
0
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1answer
78 views

Forward checking with conflict directed backjumping [closed]

Can somebody explain me how can I join forward checking with conflict directed backjumping in my CSP solver? I understand that when the consistency fails when I add a value to a variable, I should ...
0
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0answers
4 views

Hierarchical reinforcement learning exploration methods

One of the extensions to hierarchical reinforcement learning is change the degree of randomness that is applied while choosing an action. It is possible to increase the randomness to encourage ...
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0answers
42 views

A* cost implications of arbitrary/dynamic point on edge in navmesh

I currently have a working implementation of A* using navigation meshes. Agents are moving around a 3d navigation mesh, reaching their target, however often a sub-optimal path is chosen, when ...
4
votes
2answers
770 views

How is a Turing Test defined?

Turing Test definition taken from wikipedia: The Turing test is a test of a machine's ability to exhibit intelligent behavior equivalent to, or indistinguishable from, that of a human. In the ...
1
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1answer
48 views

How to properly solve this Hidden Markov Model problem?

I got a an exercise problem which should be seen as a HMM scenario and argument some statements. However I'm quite confused about how to properly solve and argument my solutions. Problem tells: ...
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0answers
35 views

Intelligent Agents-Probability and Beliefs

I am reading about probability and beliefs in artificial intelligent agents, and came across the following passage: Why the axioms of probability are reasonable The axioms of probability can ...
0
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1answer
64 views

Find path to point and avoid bear

I'm so far a self taught programmer who's mostly been working on simple web and app development. But now my teacher wants me to enter a school competition in programming. Of course the competition is ...
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1answer
21 views

ANN architectures that perform faster/efficient prediction over time?

ANN when compared to biological neural systems have this common concept of reducing error in prediction over time (training) and becoming more good at predicting correctly. But there is one behavior ...
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1answer
39 views

Understanding A* Search on Tropical Island

I am working on an online course on AI and I am now working to understand A* better. Basically, right now I am working on a problem where: we live on a tropical island and we're trying to navigate ...
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0answers
112 views

Mini-Games for Artificial Intelligence Course [closed]

I am going to have Introduction to Artificial Intelligence in this semester & I know that our main resource would be "Artificial Intelligence A Modern Approach", since I want to learn deeply and ...
0
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0answers
8 views

Hierarchical learning in a non-static environment

I've been reading about hierarchical reinforcement learning (HRL), in particular it's application to a simple delivery task as show here. While reading the paper, I noticed that the environment ...
2
votes
1answer
77 views

Is there a program that will tell you the optimal algorithm for ANY problem if the problem is decidable? [duplicate]

Is there a program that will tell you the optimal algorithm for ANY problem if the problem is decidable? If not, why not? If yes, how can such a program be realistically constructed? I would prefer ...
5
votes
3answers
258 views

Difference between weak and strong AI

I'm trying to understand the difference between weak and strong AI. For an example, let's say we would pass the turing test - would it show strong AI or weak AI then? I don't believe that this is ...
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1answer
69 views

Automatically generate meaningful queries for a data table

My field of research is not Database or AI. But I have some problems to solve, and would like to know which branch this kind of problems belong to, and what are the results. The main question is: ...
2
votes
2answers
64 views

Is it possible to implement a Neural Network using a graph data structure?

I'm trying to implement a feedforward neural network using a graph. The thing is: I haven't found any example in which is used a graph data structure. So far the examples I've found used arrays. Can ...
1
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1answer
47 views

Generating hard puzzles for a backtracking snake

Let $M$ be a matrix of height $h$ and width $w$. Each entry of $M$ is an integer. There is a snake that starts from the "left side" of $M$, and its goal is to reach the "right side" of $M$. To get ...
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0answers
53 views

Activity prediction in a kitchen

Here is the scenario: There are three chefs(A- main chef, B and C- assistant) working together to prepare a diner set. The sequence of the event is as following. Start: The three chefs enter the ...
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3answers
85 views

Are neural networks dynamical systems?

Dynamical systems are those whose evolution can be described by a rule, evolves with time and is deterministic. In this context can I say that Neural networks have a rule of evolution which is the ...
2
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1answer
53 views

Closed form solution for a single layer linear perceptron

Let f be a one-layer neural network which is linear (ie. no activation function). Let it have $p$ inputs and $q$ outputs. These are fully connected by weights $W$. We have $n$ inputs $x \in ...
1
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1answer
80 views

What are practical applications of AI Planning? [closed]

note: any tips toward making this more constructive will be highly appreciated. I've dealt with ai-related problems, from searching algorithms, to computer vision, to machine learning. However none ...
1
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1answer
257 views

Understanding Decision Stump in Adaboost

I am trying to understand how Adaboost works, and many of the tutorials online involve the use of a decision tree stump. For example, http://www.cc.gatech.edu/~thad/6601-gradAI-fall2013/boosting.pdf ...
2
votes
1answer
40 views

Why does ε-greedy $Q$-learning not oscillate?

I have a intuitive question on the convergence of $Q$- learning. In $Q$ learning for each step a $Q$- value is learned for the state-action pair where the action is selected according to the ...
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0answers
61 views

What is the difference between “objective function”, “error function”, “criterion function” and “cost function” in the context of neural networks?

The title says it all: I have seen three functions so far, that seem to be the same / similar: error function criterion function cost function objective function I am currently working on ...
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1answer
19 views

Training Error & Convergence to True Error

I Take some online class for Machine Learning. one of teacher say this sentence. if we have m data points, the training error converges to the true error as m → ∞. i thought, this sentence not ...
0
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1answer
44 views

VC Dimension Calculation for Intervals

As i See in ML Course a VC dimension calculation is very theoretical. What is the VC-dimension of intervals in R? The target function is specifieed by an interval, and labels any example positive ...
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3answers
175 views

Over-fitting Always Occurs?

i get stuck in one sentence in machine learning. i read tom Mitchel book on ML, and some other materials. if we have small training set, always over-fit can occurs? or is likely to occurs? i read ...
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1answer
43 views

Policy function π in Reinforcement learning unclear

I have one question about policy function in Reinforcement learning. in fact this function indicates which action should be done in each state? Or this function indicate for get the ...
1
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1answer
26 views

Matching training with Neural Network

I have a matching algorithm that is based on making an comparison score. This score is divided into parts. Example: 5 - Points for attributes (lets say they have 3 common attributes, would the score ...