An Architecture for Resource Bounded Agents
... actions and interleaving their execution with planning activity. In particular, executing them at the right time allows the agent to greatly simplify its subsequent planning process — it no longer needs to take into account the vast number of possible situations which would be inconsistent with newl ...
... actions and interleaving their execution with planning activity. In particular, executing them at the right time allows the agent to greatly simplify its subsequent planning process — it no longer needs to take into account the vast number of possible situations which would be inconsistent with newl ...
CSC 506: Software Engineering and Knowledge Engineering
... A particular kind of knowledge-based system One in which the knowledge, stored in the knowledge base, has been taken from an expert in some particular field. ...
... A particular kind of knowledge-based system One in which the knowledge, stored in the knowledge base, has been taken from an expert in some particular field. ...
Training a Cognitive Agent to Acquire and Represent Knowledge
... through semantic approximation, learning can benefit from an expanding state space. CA learning to acquire information, cannot afford to perform random actions (e.g., Monte-Carlo search) as part of the Markov Decision Process (MDP) used by RL, as this leads to poor performance or slow convergence [8 ...
... through semantic approximation, learning can benefit from an expanding state space. CA learning to acquire information, cannot afford to perform random actions (e.g., Monte-Carlo search) as part of the Markov Decision Process (MDP) used by RL, as this leads to poor performance or slow convergence [8 ...
The BICA Cognitive Decathlon
... multi-component objects which can be redeemed for reward once completed. Components of the objects will be distributed in systematic ways probabilistically through the environment, and the agent will receive a reward when redeemed. Some objects may be easy to construct but produce small rewards; oth ...
... multi-component objects which can be redeemed for reward once completed. Components of the objects will be distributed in systematic ways probabilistically through the environment, and the agent will receive a reward when redeemed. Some objects may be easy to construct but produce small rewards; oth ...
Normative schemas
... frames. I strongly believe that it results in most useful theory of norms. It is because such theory operates on frames developed by cognitive science, the science concerning human mind to a largest extent among other disciplines. At the beginning I briefly call the relatively short history of moder ...
... frames. I strongly believe that it results in most useful theory of norms. It is because such theory operates on frames developed by cognitive science, the science concerning human mind to a largest extent among other disciplines. At the beginning I briefly call the relatively short history of moder ...
The challenge of complexity for cognitive systems
... complexity of problems associated with this model. Thereby, they provide insights on conditions under which analogical generalization can be done efficiently. New formal approaches and new algorithms might offer a challenge to existing cognitive systems and trigger their extension and modification t ...
... complexity of problems associated with this model. Thereby, they provide insights on conditions under which analogical generalization can be done efficiently. New formal approaches and new algorithms might offer a challenge to existing cognitive systems and trigger their extension and modification t ...
Artificial Intelligence Applications by
... Only the last topic will not be covered in this course as it appears in SCAs. Knowledge–based systems can solve problems for humans or help produce solutions. They can advise users on what to do in certain situations or suggest other possible lines of attack to the problem. The successful systems ar ...
... Only the last topic will not be covered in this course as it appears in SCAs. Knowledge–based systems can solve problems for humans or help produce solutions. They can advise users on what to do in certain situations or suggest other possible lines of attack to the problem. The successful systems ar ...
A Heuristic for Hybrid Planning With Preferences Pascal Bercher
... [1] Susanne Biundo and Bernd Schattenberg. From abstract crisis to concrete relief (a preliminary report on combining state abstraction and HTN planning). In Proc. of the 6th European Conference on Planning (ECP 2001), pages 157–168, 2001. [2] Avrim L. Blum and Merrick L. Furst. Fast planning throug ...
... [1] Susanne Biundo and Bernd Schattenberg. From abstract crisis to concrete relief (a preliminary report on combining state abstraction and HTN planning). In Proc. of the 6th European Conference on Planning (ECP 2001), pages 157–168, 2001. [2] Avrim L. Blum and Merrick L. Furst. Fast planning throug ...
Mapping Between Agent Architectures and Brain Organization
... support for the requirements of such artificial systems, and indirectly, by providing another AI model of biological intelligence . effectively requires decomposition into modules and hierarchy (see [10] for discussion and references.) This requirement is not theoretical, but practical. In theory, m ...
... support for the requirements of such artificial systems, and indirectly, by providing another AI model of biological intelligence . effectively requires decomposition into modules and hierarchy (see [10] for discussion and references.) This requirement is not theoretical, but practical. In theory, m ...
SatPlan: Planning as Satisfiability
... and implemented for PDDL input in the Blackbox system (Kautz & Selman 1999). Like Blackbox, SatPlan2006 accepts the STRIPS subset of PDDL and finds solutions with minimal parallel length: that is, many (non-interfering) actions may occur in parallel at each time step, and the total number of time st ...
... and implemented for PDDL input in the Blackbox system (Kautz & Selman 1999). Like Blackbox, SatPlan2006 accepts the STRIPS subset of PDDL and finds solutions with minimal parallel length: that is, many (non-interfering) actions may occur in parallel at each time step, and the total number of time st ...
Verifying time, memory and communication bounds in systems of
... communication in systems of distributed reasoning agents. We assume that the agents reason using resolution. However this is not essential for the results in the paper, and we briefly sketch how reasoners using other inference methods can be formalised. We introduce a novel epistemic logic, BMCL-CTL ...
... communication in systems of distributed reasoning agents. We assume that the agents reason using resolution. However this is not essential for the results in the paper, and we briefly sketch how reasoners using other inference methods can be formalised. We introduce a novel epistemic logic, BMCL-CTL ...
Road Map - Computer Science Department
... Use of agreed protocols and languages Standard, agent-specific design methodologies Open agent systems in specific domains (such as in bioinformatics and e-commerce) More general scalability, arbitrary numbers and diversity of agents in each such domain Bridging agents translating between domain ...
... Use of agreed protocols and languages Standard, agent-specific design methodologies Open agent systems in specific domains (such as in bioinformatics and e-commerce) More general scalability, arbitrary numbers and diversity of agents in each such domain Bridging agents translating between domain ...
View PDF - CiteSeerX
... domain, which has lead to the appearance of the MAS approach. The rst attempts to solve problems cooperatively can be found in the seventies [FERB91a]. One of the rst of these attempts was the HEARSAY-II project [ERMA80], a speech understanding system which introduced the Blackboard model [ENGE88] ...
... domain, which has lead to the appearance of the MAS approach. The rst attempts to solve problems cooperatively can be found in the seventies [FERB91a]. One of the rst of these attempts was the HEARSAY-II project [ERMA80], a speech understanding system which introduced the Blackboard model [ENGE88] ...
Knowledge Representation and Reasoning
... Knowledge is necessary for intelligent behavior (human beings, robots). In this course we consider representation of knowledge and how we can use it in making intelligent artifacts. What is knowledge? ...
... Knowledge is necessary for intelligent behavior (human beings, robots). In this course we consider representation of knowledge and how we can use it in making intelligent artifacts. What is knowledge? ...
WHAT IS ARTIFICIAL INTELLIGENCE? Cognitive simulation
... Fundamental Subfields of AI Questions to Ask Given the goal to implement rational action in a complex environment, as in each part. . . ...
... Fundamental Subfields of AI Questions to Ask Given the goal to implement rational action in a complex environment, as in each part. . . ...
Artificial Intelligence
... bootstrapped with some knowledge. Some of this knowledge may have been heuristic in its content and encoded in the form of a production rule. A heuristic is like a "rule of thumb," and a production is an "If x then do y" kind of rule. So, for example, Sunny might be bootstrapped with the knowledge t ...
... bootstrapped with some knowledge. Some of this knowledge may have been heuristic in its content and encoded in the form of a production rule. A heuristic is like a "rule of thumb," and a production is an "If x then do y" kind of rule. So, for example, Sunny might be bootstrapped with the knowledge t ...
Document
... The wumpus world is a grid of squares surrounded by walls, where each square can contain agents and objects. The agent always starts in the lower left corner, a square that we will label [1,1]. The agent’s task is to find the gold, return to [1,1] and climb out of the cave. ...
... The wumpus world is a grid of squares surrounded by walls, where each square can contain agents and objects. The agent always starts in the lower left corner, a square that we will label [1,1]. The agent’s task is to find the gold, return to [1,1] and climb out of the cave. ...
Dimensions of Interaction
... particular pair of agents might not always be easy, or even possible. In such cases, communication can be facilitated by interposing a mediating agent. The second dimension of interaction is coordination. With multiple agents with multiple active goals, progress requires agents to share resources an ...
... particular pair of agents might not always be easy, or even possible. In such cases, communication can be facilitated by interposing a mediating agent. The second dimension of interaction is coordination. With multiple agents with multiple active goals, progress requires agents to share resources an ...
Eye on the Prize - Stanford Artificial Intelligence Laboratory
... with the basic problems of AI (or even with the basic problems of computer science). AI faculty, competing in these departments for recognition and tenure, want to be perceived as working on real problems—not chasing illdefined and far-off will-o’-the-wisps. The importance that is attached to being ...
... with the basic problems of AI (or even with the basic problems of computer science). AI faculty, competing in these departments for recognition and tenure, want to be perceived as working on real problems—not chasing illdefined and far-off will-o’-the-wisps. The importance that is attached to being ...
Knowledge-Based Systems: Concepts, Techniques
... Systems that are the focus of such wide interest today. These systems are at the applied edge of research in Artificial Intelligence. To put them in perspective this course will take a short historical tour through the AI field and its related subtopics. This tour will focus on underlying themes, wi ...
... Systems that are the focus of such wide interest today. These systems are at the applied edge of research in Artificial Intelligence. To put them in perspective this course will take a short historical tour through the AI field and its related subtopics. This tour will focus on underlying themes, wi ...
1994-Learning to Coordinate without Sharing Information
... adapt to changing environments. In this paper, we discuss how reinforcement learning techniques of developing policies to optimize environmental feedback, through a mapping between perceptions and actions, can be used by multiple agents to learn coordination strategies without having to rely on shar ...
... adapt to changing environments. In this paper, we discuss how reinforcement learning techniques of developing policies to optimize environmental feedback, through a mapping between perceptions and actions, can be used by multiple agents to learn coordination strategies without having to rely on shar ...
Some Approaches to Knowledge Acquisition
... knowledge source into a program. In our research, we have identified three different stages of knowledge acquisition and are examining different kinds of learning appropriate to each stage. We have given the chess labels of the “opening,” “middle game,” and “end game” to these stages (see Chapter 5 ...
... knowledge source into a program. In our research, we have identified three different stages of knowledge acquisition and are examining different kinds of learning appropriate to each stage. We have given the chess labels of the “opening,” “middle game,” and “end game” to these stages (see Chapter 5 ...
Using Expectations to Drive Cognitive Behavior
... for each person previously identified. It then assigns each location from perception to a person by picking the person closest to that location. If a location is left over (i.e., all known persons have been assigned to locations), a new person is identified at that location. ACT-R’s partial matching ...
... for each person previously identified. It then assigns each location from perception to a person by picking the person closest to that location. If a location is left over (i.e., all known persons have been assigned to locations), a new person is identified at that location. ACT-R’s partial matching ...
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.