Universal Artificial Intelligence
... - coincides (always?) with our intuitive guess -or- even better, - which is (in some sense) most likely the best or correct answer? • Yes! Occam’s razor: Use the simplest explanation consistent with past data (and use it for prediction). • Works! For examples presented and for many more. • Actually ...
... - coincides (always?) with our intuitive guess -or- even better, - which is (in some sense) most likely the best or correct answer? • Yes! Occam’s razor: Use the simplest explanation consistent with past data (and use it for prediction). • Works! For examples presented and for many more. • Actually ...
Pardis, a Fuzzy Extension to Multi agent Simulation Systems
... Fuzzy approach has been shown to be useful in various applications, particularly in real world problems such as artificial intelligence and complex systems. With this background, a plan for enhancing simulation environments using fuzzy tools has been proposed. For this purpose we have chosen the Rob ...
... Fuzzy approach has been shown to be useful in various applications, particularly in real world problems such as artificial intelligence and complex systems. With this background, a plan for enhancing simulation environments using fuzzy tools has been proposed. For this purpose we have chosen the Rob ...
Analyzing Impact of AI Tools on Traditional Workflow Systems
... 5. INTELLIGENT AGENT An intelligent agent is a set of independent software tools or components linked with other applications and database running on one or several computer environments. [9] Hewitt in 1977, describes the agent for the first time in its Actor Model. According to Hewitt, agent is a s ...
... 5. INTELLIGENT AGENT An intelligent agent is a set of independent software tools or components linked with other applications and database running on one or several computer environments. [9] Hewitt in 1977, describes the agent for the first time in its Actor Model. According to Hewitt, agent is a s ...
Artificial Intelligence – Agents and Environments
... winds (to point out its dynamic nature). Yet another analogy might be to liken it to the ephemeral nature of clouds, also controlled by the prevailing winds, but whose substance is impossible to grasp, being forever out of reach (to show the difficulty in defining it). These analogies are rich in me ...
... winds (to point out its dynamic nature). Yet another analogy might be to liken it to the ephemeral nature of clouds, also controlled by the prevailing winds, but whose substance is impossible to grasp, being forever out of reach (to show the difficulty in defining it). These analogies are rich in me ...
Affordances for robots: a brief survey
... is treated as an exception that is usually hand led by explicit re-planning. With the uncertainty and unpredictability inherent in the real world, these aspects can limit the versatility of physical robots. These challenges have been addressed by researchers through refinements such as modeling unce ...
... is treated as an exception that is usually hand led by explicit re-planning. With the uncertainty and unpredictability inherent in the real world, these aspects can limit the versatility of physical robots. These challenges have been addressed by researchers through refinements such as modeling unce ...
Dynamic Potential-Based Reward Shaping
... converge to a Nash equilibrium [18]. To model a MAS, the single-agent MDP becomes inadequate and instead the more general Stochastic Game (SG) is required [5]. A SG of n agents is a tuple hS, A1 , ..., An , T, R1 , ..., Rn i, where S is the state space, Ai is the action space of agent i, T (s, ai... ...
... converge to a Nash equilibrium [18]. To model a MAS, the single-agent MDP becomes inadequate and instead the more general Stochastic Game (SG) is required [5]. A SG of n agents is a tuple hS, A1 , ..., An , T, R1 , ..., Rn i, where S is the state space, Ai is the action space of agent i, T (s, ai... ...
Intelligent Agent Technology and Application
... ”Autonomous agents are computational systems that inhabit some complex dynamic environment, sense and act autonomously in this environment, and by doing so realize a set of goals or tasks for which they are designed”. ...
... ”Autonomous agents are computational systems that inhabit some complex dynamic environment, sense and act autonomously in this environment, and by doing so realize a set of goals or tasks for which they are designed”. ...
Intelligent Agent Technology and Application
... ”Autonomous agents are computational systems that inhabit some complex dynamic environment, sense and act autonomously in this environment, and by doing so realize a set of goals or tasks for which they are designed”. ...
... ”Autonomous agents are computational systems that inhabit some complex dynamic environment, sense and act autonomously in this environment, and by doing so realize a set of goals or tasks for which they are designed”. ...
affordance - Aleksandra Derra
... by perceiving the world around them. By exploiting the relationship between the agent and its environment, designers can reduce the need for an agent to construct and maintain complex internal representations; designers can instead focus on the details of how the agent interacts directly with the en ...
... by perceiving the world around them. By exploiting the relationship between the agent and its environment, designers can reduce the need for an agent to construct and maintain complex internal representations; designers can instead focus on the details of how the agent interacts directly with the en ...
Assigning agents to a line
... to the four applicants given their preferences? We analyze in this paper assignment problems like the one above. More precisely, we consider situations where there is a finite number of agents, each with a preferred slot, caring only about the gap between their assigned slot and their preferred slot ...
... to the four applicants given their preferences? We analyze in this paper assignment problems like the one above. More precisely, we consider situations where there is a finite number of agents, each with a preferred slot, caring only about the gap between their assigned slot and their preferred slot ...
Measurements of collective machine intelligence
... Also, with respect to the evaluation of machine intelligence, some advancement has been made. The Turing Test expresses how far a computer is able to resemble a human. It is named after its famous inventor who was very concerned with machine intelligence already in 1950. Turing [57] asked for instan ...
... Also, with respect to the evaluation of machine intelligence, some advancement has been made. The Turing Test expresses how far a computer is able to resemble a human. It is named after its famous inventor who was very concerned with machine intelligence already in 1950. Turing [57] asked for instan ...
Task Coordination for Non-cooperative Planning Agents
... Figure 1, the task network has been completed if both t1 and t2 have been completed and these tasks can be completed by e.g. performing the tasks t111 , t12 , t21 , t221 , t222 and t23 . Note that the model presented here differs from most other hierarchical task frameworks in the sense that we do n ...
... Figure 1, the task network has been completed if both t1 and t2 have been completed and these tasks can be completed by e.g. performing the tasks t111 , t12 , t21 , t221 , t222 and t23 . Note that the model presented here differs from most other hierarchical task frameworks in the sense that we do n ...
Introduction to Artificial Intelligence
... Performance measure: An objective criterion for success of an agent's behavior, given the evidence provided by the percept sequence. A performance measure for a vacuum-cleaner agent might include one or more of: • +1 point for each clean square in time T • +1 point for clean square, -1 for each ...
... Performance measure: An objective criterion for success of an agent's behavior, given the evidence provided by the percept sequence. A performance measure for a vacuum-cleaner agent might include one or more of: • +1 point for each clean square in time T • +1 point for clean square, -1 for each ...
Accepting Optimally in Automated Negotiation with Incomplete
... to end or to continue the negotiation? Of course, A’s decision making process will depend on the current offer, as well as the offers that A can expect to receive from B in the future. However, in most realistic cases, agents have only incomplete information about each other [5, 9, 15]. In this pape ...
... to end or to continue the negotiation? Of course, A’s decision making process will depend on the current offer, as well as the offers that A can expect to receive from B in the future. However, in most realistic cases, agents have only incomplete information about each other [5, 9, 15]. In this pape ...
Artificial Intelligence, Second Edition
... For any phenomenon, you can distinguish real versus fake, where the fake is non-real. You can also distinguish natural versus artificial. Natural means occurring in nature and artificial means made by people. Example 1.1 A tsunami is a large wave in an ocean. Natural tsunamis occur from time to time ...
... For any phenomenon, you can distinguish real versus fake, where the fake is non-real. You can also distinguish natural versus artificial. Natural means occurring in nature and artificial means made by people. Example 1.1 A tsunami is a large wave in an ocean. Natural tsunamis occur from time to time ...
Intelligent Agents - Department of Computer Science, Oxford
... like the question what is intelligence? itself, is not an easy one to answer. But for me, an intelligent agent is one that is capable of flexible autonomous action in order to meet its design objectives, where by flexible, I mean three things [71]: reactivity: intelligent agents are able to perceive ...
... like the question what is intelligence? itself, is not an easy one to answer. But for me, an intelligent agent is one that is capable of flexible autonomous action in order to meet its design objectives, where by flexible, I mean three things [71]: reactivity: intelligent agents are able to perceive ...
The Importance of Cognitive Architectures
... Although this level concerns intra-agent processes, computational cognitive models (cognitive architectures) developed therein may be used to capture processes at higher levels, including interaction at a sociological level whereby multiple individuals are involved. This can be accomplished, for exa ...
... Although this level concerns intra-agent processes, computational cognitive models (cognitive architectures) developed therein may be used to capture processes at higher levels, including interaction at a sociological level whereby multiple individuals are involved. This can be accomplished, for exa ...
Multiagent Reinforcement Learning With Unshared Value Functions
... Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TCYB.2014.2332042 ...
... Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TCYB.2014.2332042 ...
Decentralized POMDPs
... Previous chapters generalized decision making to multiple agents (Chapter ??) and to acting under state uncertainty as in POMDPs (Chapter ??). This chapter generalizes further by considering situations with both state uncertainty and multiple agents. In particular, it focuses on teams of collaborati ...
... Previous chapters generalized decision making to multiple agents (Chapter ??) and to acting under state uncertainty as in POMDPs (Chapter ??). This chapter generalizes further by considering situations with both state uncertainty and multiple agents. In particular, it focuses on teams of collaborati ...
I Agents, Bodies, Constraints, Dynamics, and Evolution Alan K. Mackworth
... consistency, then path consistency, then k-consistency, and so on. Many other AI researchers contributed to this development, including Richard Fikes, Dave Waltz, Ugo Montanari, and Eugene Freuder. For a detailed historical perspective on that development see Freuder and Mackworth (2006). Since thos ...
... consistency, then path consistency, then k-consistency, and so on. Many other AI researchers contributed to this development, including Richard Fikes, Dave Waltz, Ugo Montanari, and Eugene Freuder. For a detailed historical perspective on that development see Freuder and Mackworth (2006). Since thos ...
Agents - PNU-CS-AI
... o Often, percepts alone are insufficient to decide what to do. o This is because the correct action depends on the given explicit goals (e.g., go towards X). o The goal-based agents use an explicit representation of goals and consider them for the choice of actions. o Ex : taxi driving destination , ...
... o Often, percepts alone are insufficient to decide what to do. o This is because the correct action depends on the given explicit goals (e.g., go towards X). o The goal-based agents use an explicit representation of goals and consider them for the choice of actions. o Ex : taxi driving destination , ...