Towards a Logic of Rational Agency
... huge coordinated organization, you’ll get something that has properties on another level. You can see it – in fact you have to see it– not as a bunch of little calculations, but as a system of tendencies and desires and beliefs and so on. When things get complicated enough, you’re forced to change y ...
... huge coordinated organization, you’ll get something that has properties on another level. You can see it – in fact you have to see it– not as a bunch of little calculations, but as a system of tendencies and desires and beliefs and so on. When things get complicated enough, you’re forced to change y ...
Towards a Logic of Rational Agency
... coordinated organization, you’ll get something that has properties on another level. You can see it – in fact you have to see it– not as a bunch of little calculations, but as a system of tendencies and desires and beliefs and so on. When things get complicated enough, you’re forced to change your l ...
... coordinated organization, you’ll get something that has properties on another level. You can see it – in fact you have to see it– not as a bunch of little calculations, but as a system of tendencies and desires and beliefs and so on. When things get complicated enough, you’re forced to change your l ...
Analyzing Myopic Approaches for Multi
... about another agent’s state through a non-communicative act. This communication is often represented within the transition function and is difficult to quantify. For example, a robot attempts to move forward and fails. The failure could be caused by the wheels spinning in place or by another robot s ...
... about another agent’s state through a non-communicative act. This communication is often represented within the transition function and is difficult to quantify. For example, a robot attempts to move forward and fails. The failure could be caused by the wheels spinning in place or by another robot s ...
Lifelong Multi-Agent Path Finding for Online Pickup
... storage locations to packing stations. Past research efforts have concentrated mostly on a “one-shot” version of this problem, called the multi-agent path-finding (MAPF) problem, which has been studied in artificial intelligence, robotics, and operations research. In the MAPF problem, each agent has ...
... storage locations to packing stations. Past research efforts have concentrated mostly on a “one-shot” version of this problem, called the multi-agent path-finding (MAPF) problem, which has been studied in artificial intelligence, robotics, and operations research. In the MAPF problem, each agent has ...
Strawson`s take on moral responsibility applied to Intelligent Systems
... by definition not totally controlled by other agents, since the agent would then not be autonomous. The actions of the agent cannot be understood as random, but must be understood as part of a plan, a goal or an intention to act and knowingly cause consequences. It is this interpretation of intellig ...
... by definition not totally controlled by other agents, since the agent would then not be autonomous. The actions of the agent cannot be understood as random, but must be understood as part of a plan, a goal or an intention to act and knowingly cause consequences. It is this interpretation of intellig ...
Learning to Evaluate Conditional Partial Plans
... trying to find out which is the most useful one to perform. For this paper, Actor waits until Deductor terminates and only executes plans after this happens, but in general it is Actor’s responsibility to balance acting and deliberation. Finally, the Learner module analyses the agent’s past experien ...
... trying to find out which is the most useful one to perform. For this paper, Actor waits until Deductor terminates and only executes plans after this happens, but in general it is Actor’s responsibility to balance acting and deliberation. Finally, the Learner module analyses the agent’s past experien ...
A Case Study in Developmental Robotics
... situations where different places the agents is found at, collapse into the same sensory image S (e.g. if the agent is facing a corner of the room, which corner is that?) The problem, known as perceptual aliasing problem is a common one. For example, in an article (Barto et al., 1995) it was shown t ...
... situations where different places the agents is found at, collapse into the same sensory image S (e.g. if the agent is facing a corner of the room, which corner is that?) The problem, known as perceptual aliasing problem is a common one. For example, in an article (Barto et al., 1995) it was shown t ...
The Behavior-Oriented Design of Modular Agent Intelligence
... This chapter examines how to build complete, complex agents (CCA). A complete agent is an agent that can function naturally on its own, rather than being a dependent part of a Multi-Agent System (MAS). A complex agent is one that has multiple, conflicting goals, and multiple, mutually-exclusive mean ...
... This chapter examines how to build complete, complex agents (CCA). A complete agent is an agent that can function naturally on its own, rather than being a dependent part of a Multi-Agent System (MAS). A complex agent is one that has multiple, conflicting goals, and multiple, mutually-exclusive mean ...
Narrative Intelligence - Carnegie Mellon School of Computer Science
... behaviors. Because of this design choice, a behavior, when turned on, does not know why it is turned on, who was turned on before it, or even who else is ...
... behaviors. Because of this design choice, a behavior, when turned on, does not know why it is turned on, who was turned on before it, or even who else is ...
CMPUT 650: Learning To Make Decisions
... A hunt the Wumpus flash version: http://www.flashrolls.com/puzzlegames/Hunt-The-Wumpus-Flash-Game.htm ...
... A hunt the Wumpus flash version: http://www.flashrolls.com/puzzlegames/Hunt-The-Wumpus-Flash-Game.htm ...
Towards Adversarial Reasoning in Statistical Relational Domains
... “better” labeling than the true labels. Following Equation 2, this can be solved by standard MAP inference in an MLN. Adversarial relational reasoning can also be used to develop adversarially robust learning methods. For example, suppose we wish to learn the parameters of a webspam classification s ...
... “better” labeling than the true labels. Following Equation 2, this can be solved by standard MAP inference in an MLN. Adversarial relational reasoning can also be used to develop adversarially robust learning methods. For example, suppose we wish to learn the parameters of a webspam classification s ...
Motivated_Learning_BARCELONA
... Machine creates abstract goals based on the primitive pain signals. ...
... Machine creates abstract goals based on the primitive pain signals. ...
Using Distributed Data Mining and Distributed Artificial
... where it came from as well as the other agents which also hold it to exclude it from their rules set. After all rules in all agents have been analyzed, they must be tested against each agent’ s validation set (10%). The agent’ s rules whose accuracy against its validation set is the highest will int ...
... where it came from as well as the other agents which also hold it to exclude it from their rules set. After all rules in all agents have been analyzed, they must be tested against each agent’ s validation set (10%). The agent’ s rules whose accuracy against its validation set is the highest will int ...
Approximate Solutions For Partially Observable Stochastic Games
... a policy σi for each agent that defines a probability distribution over the actions it should take at each timestep. We will use the Pareto-optimal Nash equilibrium as our solution concept for POSGs with common payoffs. A Nash equilibrium of a game is a set of strategies (or policies) for each agent ...
... a policy σi for each agent that defines a probability distribution over the actions it should take at each timestep. We will use the Pareto-optimal Nash equilibrium as our solution concept for POSGs with common payoffs. A Nash equilibrium of a game is a set of strategies (or policies) for each agent ...
John McCarthy defines artificial intelligence as
... This website has contents dealing with agents that include definitions, readings, and subtopics. The subtopics content include links to multi-agent systems, websearching agents and the semantic web, and social media. This website is laid out nicely and contains many interesting links to other pages ...
... This website has contents dealing with agents that include definitions, readings, and subtopics. The subtopics content include links to multi-agent systems, websearching agents and the semantic web, and social media. This website is laid out nicely and contains many interesting links to other pages ...
A NEW REAL TIME LEARNING ALGORITHM 1. Introduction One
... One characteristic of the algorithm is that the agent determines the next action in a constant time. That is why this algorithm is called an on-line, real-time search algorithm. The function that gives the initial values of h0 is called a heuristic function. A heuristic function is called admissible ...
... One characteristic of the algorithm is that the agent determines the next action in a constant time. That is why this algorithm is called an on-line, real-time search algorithm. The function that gives the initial values of h0 is called a heuristic function. A heuristic function is called admissible ...
Universal Artificial Intelligence: Practical Agents and Fundamental
... IV. Is there any guarantee that following these principles will lead to good learning performance? Computer programs. The solution to these questions come from a somewhat unexpected direction. In one of the greatest mathematical discoveries of the 20th century, Alan Turing invented the universal Tur ...
... IV. Is there any guarantee that following these principles will lead to good learning performance? Computer programs. The solution to these questions come from a somewhat unexpected direction. In one of the greatest mathematical discoveries of the 20th century, Alan Turing invented the universal Tur ...
Intelligent Agent Technology and Application
... G. M. P. O'Hare and N. R. Jennings, editors. "Foundations of ...
... G. M. P. O'Hare and N. R. Jennings, editors. "Foundations of ...
Intelligent Agent Technology and Application
... G. M. P. O'Hare and N. R. Jennings, editors. "Foundations of ...
... G. M. P. O'Hare and N. R. Jennings, editors. "Foundations of ...
Conflict-Based Search For Optimal Multi
... given a graph, G(V, E), and a set of k agents labeled a1 . . . ak . Each agent ai has a start position si ∈ V and goal position gi ∈ V . At each time step an agent can either move to a neighboring location or can wait in its current location. The task is to return a set of actions for each agent, th ...
... given a graph, G(V, E), and a set of k agents labeled a1 . . . ak . Each agent ai has a start position si ∈ V and goal position gi ∈ V . At each time step an agent can either move to a neighboring location or can wait in its current location. The task is to return a set of actions for each agent, th ...
Computing Shapley values manipulating value division schemes and checking core membership in multi-issue domains
... even if we can compute each coalition’s value, we still need a method to choose a value division among the agents that is consistent with the solution concept. Finding such a value division can be a nontrivial problem. How complex is it? There are other, related, important computational questions as ...
... even if we can compute each coalition’s value, we still need a method to choose a value division among the agents that is consistent with the solution concept. Finding such a value division can be a nontrivial problem. How complex is it? There are other, related, important computational questions as ...
Teachable agents 2
... suggests a different one, it will reject the user – This irritated the users ...
... suggests a different one, it will reject the user – This irritated the users ...
Non-Optimal Multi-Agent Pathfinding Is Solved (Since 1984)
... One reason why the work by Kornhauser, Miller, and Spirakis fell a bit into oblivion could be that the only archival publication is very sketchy and often refers to a “final version” which never appeared. However, all results are described in detail in Kornhauser’s master’s thesis, which is availabl ...
... One reason why the work by Kornhauser, Miller, and Spirakis fell a bit into oblivion could be that the only archival publication is very sketchy and often refers to a “final version” which never appeared. However, all results are described in detail in Kornhauser’s master’s thesis, which is availabl ...
Intelligent Agent Technology and Application
... G. M. P. O'Hare and N. R. Jennings, editors. "Foundations of Distributed AI". ...
... G. M. P. O'Hare and N. R. Jennings, editors. "Foundations of Distributed AI". ...
From Reaction To Cognition: 5th European Workshop On Modelling
... _in_Artificial_Intelligence_and_Applications_.pdf Download legal documents CiteSeerX Citation Query editors. From Reaction editors. From Reaction to Cognition. Documents; Authors; Tables; Log in; Sign up; MetaCart; Donate; 5th European Workshop on Modelling Autonomous Agents in a " Switzerland)" dow ...
... _in_Artificial_Intelligence_and_Applications_.pdf Download legal documents CiteSeerX Citation Query editors. From Reaction editors. From Reaction to Cognition. Documents; Authors; Tables; Log in; Sign up; MetaCart; Donate; 5th European Workshop on Modelling Autonomous Agents in a " Switzerland)" dow ...