記錄編號 6668 狀態 NC094FJU00392004 助教查核 索書號 學校名稱
... 式學習精煉最原始的目標(top-level goals)。 並以機器人足球比賽用來說明我們的 方法。 而且，我們顯示如何精煉以強效式學習演化目標於足球員之心智狀態 This paper presents an adaptive approach to address the goal evolution of the intelligent agent. When agents are initially created, they have some goals and few capabilities. Each capability composes by one or more act ...
... 式學習精煉最原始的目標(top-level goals)。 並以機器人足球比賽用來說明我們的 方法。 而且，我們顯示如何精煉以強效式學習演化目標於足球員之心智狀態 This paper presents an adaptive approach to address the goal evolution of the intelligent agent. When agents are initially created, they have some goals and few capabilities. Each capability composes by one or more act ...
AI and Agents
... AI: study of rational agents A rational agent carries out an action with the best outcome after considering past and current percepts ...
... AI: study of rational agents A rational agent carries out an action with the best outcome after considering past and current percepts ...
Incremental Learning with Partial Instance Memory Talk Overview
... 1. Learn, say, rules from examples 2. Store rules, store examples 3. Use rules to predict, navigate, etc. 4. When new examples arrive, add to current examples 5. Goto step 1 • Incremental Learning 1. Learn rules from examples 2. Store rules, discard examples 3. Use rules to predict, navigate, etc. 4 ...
... 1. Learn, say, rules from examples 2. Store rules, store examples 3. Use rules to predict, navigate, etc. 4. When new examples arrive, add to current examples 5. Goto step 1 • Incremental Learning 1. Learn rules from examples 2. Store rules, discard examples 3. Use rules to predict, navigate, etc. 4 ...
Studiefiche - studiegids UGent
... Artificial intelligence (AI) is the study of solutions for problems that are difficult or impractical to solve with traditional methods. It is used pervasively in support of everyday applications such as email, word-processing and search, as well as in the design and analysis of autonomous agents th ...
... Artificial intelligence (AI) is the study of solutions for problems that are difficult or impractical to solve with traditional methods. It is used pervasively in support of everyday applications such as email, word-processing and search, as well as in the design and analysis of autonomous agents th ...
Knowledge Base
... What is an intelligent agent An intelligent agent is a system that: • perceives its environment (which may be the physical world, a user via a graphical user interface, a collection of other agents, the Internet, or other complex environment); • reasons to interpret perceptions, draw inferences, so ...
... What is an intelligent agent An intelligent agent is a system that: • perceives its environment (which may be the physical world, a user via a graphical user interface, a collection of other agents, the Internet, or other complex environment); • reasons to interpret perceptions, draw inferences, so ...
Chapter 1 Constrained Incrementalist Moral Decision Making for a
... avoided on the lowest level during runtime by a bottom-up emotional mechanism, which would inhibit the selection of the action if there is a negative emotional response. Emotional responses can implement values and contribute to bottom-up moral decision making (see next subsection). These would have ...
... avoided on the lowest level during runtime by a bottom-up emotional mechanism, which would inhibit the selection of the action if there is a negative emotional response. Emotional responses can implement values and contribute to bottom-up moral decision making (see next subsection). These would have ...
A Unified Cognitive Architecture for Physical Agents
... Thus, Icarus also includes a belief memory that contains higher-level inferences about the agent’s situation. Whereas percepts describe attributes of specific objects, beliefs describe relations among objects, such as the relative positions of two buildings. Each element in this belief memory consis ...
... Thus, Icarus also includes a belief memory that contains higher-level inferences about the agent’s situation. Whereas percepts describe attributes of specific objects, beliefs describe relations among objects, such as the relative positions of two buildings. Each element in this belief memory consis ...
document
... actions are appropriate for goals and circumstances to changing environments and goals learns from experience ...
... actions are appropriate for goals and circumstances to changing environments and goals learns from experience ...
Research projects & needs
... on it, over time, in pursuit of its own agenda. • It must have built in sensors, effectors, and drives, or primitive motivators. ...
... on it, over time, in pursuit of its own agenda. • It must have built in sensors, effectors, and drives, or primitive motivators. ...
A differentiable approach to inductive logic programming
... other relations for both train and test sets. During training, we ask the model to answer queries about the relation R using facts in the database. The loss is the mean squared error between the model’s answer and the true answer. The model is trained with weak supervision. Only the query input and ...
... other relations for both train and test sets. During training, we ask the model to answer queries about the relation R using facts in the database. The loss is the mean squared error between the model’s answer and the true answer. The model is trained with weak supervision. Only the query input and ...
PowerPoint - University of Virginia, Department of Computer Science
... Learning and Autonomy Learning • To update the agent function, ,in light of observed performance of percept-sequence to action pairs – Does the agent control observations? What parts of state space to explore? Learn from trial and error – How do observations affect agent function? Change inte ...
... Learning and Autonomy Learning • To update the agent function, ,in light of observed performance of percept-sequence to action pairs – Does the agent control observations? What parts of state space to explore? Learn from trial and error – How do observations affect agent function? Change inte ...
CS 561a: Introduction to Artificial Intelligence
... should eventually succeed. It is a race, but both racers seem to be walking. [John McCarthy] SE 420 ...
... should eventually succeed. It is a race, but both racers seem to be walking. [John McCarthy] SE 420 ...
Agents - Hiram College
... • Information gathering - actions that modify future percepts • Learning - modifying the program based on actions and perceived results • Autonomy - agent’s behavior depends on its own percepts, rather than designer’s programming (a priori knowledge) ...
... • Information gathering - actions that modify future percepts • Learning - modifying the program based on actions and perceived results • Autonomy - agent’s behavior depends on its own percepts, rather than designer’s programming (a priori knowledge) ...
Rule - FUMblog
... reasonably close to human reasoning can be manipulated by computers appropriate granularity knowledge “chunks” are manageable both for humans and for computers دكتر كاهاني-سيستمهاي خبره و مهندسي دانش ...
... reasonably close to human reasoning can be manipulated by computers appropriate granularity knowledge “chunks” are manageable both for humans and for computers دكتر كاهاني-سيستمهاي خبره و مهندسي دانش ...
Multiple Workspaces as an Architecture for Cognition
... There have been several attempts at unified theories of intelligence from within cognitive science. At least two of these emphasise the role of production systems. In SOAR Newell and Laird [9] proposed a production system model in which serial application of rules, written in a common form, modified ...
... There have been several attempts at unified theories of intelligence from within cognitive science. At least two of these emphasise the role of production systems. In SOAR Newell and Laird [9] proposed a production system model in which serial application of rules, written in a common form, modified ...
(1986) Remembering to do things in the laboratory and everyday life
... necessary to check the clock to see whether it is time to take the cake out. There are many everyday tasks of this kind that require periodic monitoring. The memory processes involved are far from simple and once again involve remembering to do something without being reminded. Harris & Wilkins aske ...
... necessary to check the clock to see whether it is time to take the cake out. There are many everyday tasks of this kind that require periodic monitoring. The memory processes involved are far from simple and once again involve remembering to do something without being reminded. Harris & Wilkins aske ...
Intelligence - Ohio University
... Embodied Intelligence (EI) is a mechanism that learns how to survive in a hostile environment – Mechanism: biological, mechanical or virtual agent with embodied sensors and actuators – EI acts on environment and perceives its actions – Environment hostility is persistent and stimulates EI to act – ...
... Embodied Intelligence (EI) is a mechanism that learns how to survive in a hostile environment – Mechanism: biological, mechanical or virtual agent with embodied sensors and actuators – EI acts on environment and perceives its actions – Environment hostility is persistent and stimulates EI to act – ...
notes - School of Computer Science and Statistics
... – (near optimal in some cases) – problems when the agent population is large Agent chains • New rules (“docker robots”) (Drogoul and Ferber, 1992) ...
... – (near optimal in some cases) – problems when the agent population is large Agent chains • New rules (“docker robots”) (Drogoul and Ferber, 1992) ...
Multi Agent System & Holonic Manufacturing System
... Agents have their roots in the computer science (artificial intelligence area) and the Holons in the computer integrated manufacturing domain, focusing on the problem associated with the flexible manufacturing systems ...
... Agents have their roots in the computer science (artificial intelligence area) and the Holons in the computer integrated manufacturing domain, focusing on the problem associated with the flexible manufacturing systems ...
1 - Jordan University of Science and Technology
... associate with human thinking, activities such as decision-making, problem solving, learning ...'' (Bellman, 1978) ...
... associate with human thinking, activities such as decision-making, problem solving, learning ...'' (Bellman, 1978) ...
Progress and Challenges in Interactive Cognitive Systems
... Three Hypotheses for Cognitive Systems Newell and Simon (1976) proposed two hypotheses that underlie most work on cognitive systems: • The ability to encode, manipulate, and interpret symbol structures is necessary and sufficient for general intelligent action. • Problem solving involves heuristi ...
... Three Hypotheses for Cognitive Systems Newell and Simon (1976) proposed two hypotheses that underlie most work on cognitive systems: • The ability to encode, manipulate, and interpret symbol structures is necessary and sufficient for general intelligent action. • Problem solving involves heuristi ...
THE EMOTIOGENIC BRAIN STRUCTURES IN CONDITIONING
... of multi-trial learning. However, AM-CG control is not excluded entirely. What is decisive in the regulatory function of the AM-CG system? Not its participation in the registration of reinforcement and not the evaluation of the biological meaning of the information, although they are important initi ...
... of multi-trial learning. However, AM-CG control is not excluded entirely. What is decisive in the regulatory function of the AM-CG system? Not its participation in the registration of reinforcement and not the evaluation of the biological meaning of the information, although they are important initi ...
Resources - CSE, IIT Bombay
... searching amongst the options of moving Left, Right, Up or Down. Additionally, each movement has an associated cost representing the relative difficulty of each movement. The search then will have to find the optimal, i.e., the least cost path. ...
... searching amongst the options of moving Left, Right, Up or Down. Additionally, each movement has an associated cost representing the relative difficulty of each movement. The search then will have to find the optimal, i.e., the least cost path. ...
A Modern, Agent-Oriented Approach to Introductory Artificial
... reach of the designer into unknownenvironments, and showhow it constrains agent design, favoring explicit knowledge representation and reasoning. Wetreat robotics and vision not as independently defined problems, but as occurring in the service of goal achievement. Throughout, we stress the importan ...
... reach of the designer into unknownenvironments, and showhow it constrains agent design, favoring explicit knowledge representation and reasoning. Wetreat robotics and vision not as independently defined problems, but as occurring in the service of goal achievement. Throughout, we stress the importan ...
Cross-Paradigm Analysis of Autonomous Agent Architecture
... action selection necessarily lead to rigid, brittle systems incapable of reacting quickly and opportunistically to changes in the environment. On the other hand, hierarchical and sequential control are wellestablished programming techniques that demonstrably manage enormous complexity. This section ...
... action selection necessarily lead to rigid, brittle systems incapable of reacting quickly and opportunistically to changes in the environment. On the other hand, hierarchical and sequential control are wellestablished programming techniques that demonstrably manage enormous complexity. This section ...
Soar (cognitive architecture)
Soar is a cognitive architecture, created by John Laird, Allen Newell, and Paul Rosenbloom at Carnegie Mellon University, now maintained by John Laird's research group at the University of Michigan. It is both a view of what cognition is and an implementation of that view through a computer programming architecture for artificial intelligence (AI). Since its beginnings in 1983 and its presentation in a paper in 1987, it has been widely used by AI researchers to model different aspects of human behavior.