Lecture#1 slides - Computer Science
... There is no universally accepted definition of the term agent and there is a good deal of ongoing debate and controversy on this subject The situation is somehow comparable with the one encountered when defining artificial intelligence. ...
... There is no universally accepted definition of the term agent and there is a good deal of ongoing debate and controversy on this subject The situation is somehow comparable with the one encountered when defining artificial intelligence. ...
Future and Emerging Technologies FET
... insufficient for representing our uncertain graph model; because, we introduce features that may require improvements in the representation models that current tools use. Simpler uncertain graph databases were represented using Resource Description Framework (RDF) model (Udrea, Subrahmanian, & Majki ...
... insufficient for representing our uncertain graph model; because, we introduce features that may require improvements in the representation models that current tools use. Simpler uncertain graph databases were represented using Resource Description Framework (RDF) model (Udrea, Subrahmanian, & Majki ...
ai-lect2
... • How large: size of table = #possible percepts times # possible actions = |Pl | |Pm| |Pr| |S| |B| E.g., P = {close, medium, far}3 A = {left, straight, right} {on, off} then size of table = 27*3*2 = 162 • How to select action? Search. ...
... • How large: size of table = #possible percepts times # possible actions = |Pl | |Pm| |Pr| |S| |B| E.g., P = {close, medium, far}3 A = {left, straight, right} {on, off} then size of table = 27*3*2 = 162 • How to select action? Search. ...
coppin chapter 19
... have the ability to communicate and collaborate with each other. Learning multi-agent systems can be developed, for example to control the individual limbs of a robot. An agent team is a group of agents that cooperate to achieve some common goal – such as arranging the various components of a trip: ...
... have the ability to communicate and collaborate with each other. Learning multi-agent systems can be developed, for example to control the individual limbs of a robot. An agent team is a group of agents that cooperate to achieve some common goal – such as arranging the various components of a trip: ...
Artificial Intelligence: Modern Approach
... Together, Parts II to V describe that part of the intelligent agent responsible for reaching decisions. Part VI, "Learning," describes methods for generating the knowledge required by these decision-making components; it also introduces a new kind of component, the neural network, and its associated ...
... Together, Parts II to V describe that part of the intelligent agent responsible for reaching decisions. Part VI, "Learning," describes methods for generating the knowledge required by these decision-making components; it also introduces a new kind of component, the neural network, and its associated ...
Connectionist AI, symbolic AI, and the brain
... the order of 1 min. Thus, for times less than about 100 ms, we have a single equilibration or 'settling' of the network; all the knowledge embedded in the connections is used in parallel. On this time scale, we have parallel computation. When we go beyond this, to cognitive processes that go on for ...
... the order of 1 min. Thus, for times less than about 100 ms, we have a single equilibration or 'settling' of the network; all the knowledge embedded in the connections is used in parallel. On this time scale, we have parallel computation. When we go beyond this, to cognitive processes that go on for ...
Multi-Agent Systems - AI-MAS
... NASA uses autonomous agents to handle tasks that appear simple but are actually quite complex. For example, one mission goal handled by autonomous agents is simply to not waste fuel. But accomplishing that means balancing multiple demands, such as staying on course and keeping experiments running, a ...
... NASA uses autonomous agents to handle tasks that appear simple but are actually quite complex. For example, one mission goal handled by autonomous agents is simply to not waste fuel. But accomplishing that means balancing multiple demands, such as staying on course and keeping experiments running, a ...
Structured Knowledge Representation and Schema Systems
... Kant distinguished "Phenomena" from "Noumena". Noumena is the underlying unknowable reality of the universe. Noumena can never be completely known, but only partially observed through the senses. Phenomena provide partial observation of Noumena. Thus Phenomena are necessarily imperfect. Kant propose ...
... Kant distinguished "Phenomena" from "Noumena". Noumena is the underlying unknowable reality of the universe. Noumena can never be completely known, but only partially observed through the senses. Phenomena provide partial observation of Noumena. Thus Phenomena are necessarily imperfect. Kant propose ...
Presentation
... • Bi : state abstraction function which maps state s in the original MDP into an abstract state in Mi • Ai : The set of subtasks that can be called by Mi • Gi : Termination predicate ...
... • Bi : state abstraction function which maps state s in the original MDP into an abstract state in Mi • Ai : The set of subtasks that can be called by Mi • Gi : Termination predicate ...
CV - Olivier Georgeon
... algorithms, and methods to replicate situated cognition (i.e., in which, “knowledge develops as a means of coordinating activity within activity itself”, Clancey 1997). My colleagues and I proposed the Enactive Cognitive Architecture (ECA, Georgeon, Marshall, & Manzotti, 2013). ECA avoids making ...
... algorithms, and methods to replicate situated cognition (i.e., in which, “knowledge develops as a means of coordinating activity within activity itself”, Clancey 1997). My colleagues and I proposed the Enactive Cognitive Architecture (ECA, Georgeon, Marshall, & Manzotti, 2013). ECA avoids making ...
Influence of Psychoanalytic Defense Mechanisms on the Decision
... Abstract-Conflicting goals, rules, and/or input data can cause problems in the decision making unit of software agents. Hence, in this paper we introduce psychoanalytic defense mechanisms to be implemented in multi-agent systems to resolve these conflicts. We give a general insight into defense mech ...
... Abstract-Conflicting goals, rules, and/or input data can cause problems in the decision making unit of software agents. Hence, in this paper we introduce psychoanalytic defense mechanisms to be implemented in multi-agent systems to resolve these conflicts. We give a general insight into defense mech ...
File
... Disadvantage: Disadvantage is that it does not represent states directly, so it is harder to estimate how far a partial-order plan is from achieving a goal. 5. What is a Planning graph? A Planning graph consists of a sequence of levels that correspond to time steps in the plan where level 0 is the i ...
... Disadvantage: Disadvantage is that it does not represent states directly, so it is harder to estimate how far a partial-order plan is from achieving a goal. 5. What is a Planning graph? A Planning graph consists of a sequence of levels that correspond to time steps in the plan where level 0 is the i ...
Two Paradigms Are Better Than One, And Multiple
... with a few subsidiary modules for handling exceptions or special cases. Some systems are built from components that perform different tasks, but each component is based on a single paradigm. Since people freely switch from one method of thinking or reasoning to another, some cognitive scientists bel ...
... with a few subsidiary modules for handling exceptions or special cases. Some systems are built from components that perform different tasks, but each component is based on a single paradigm. Since people freely switch from one method of thinking or reasoning to another, some cognitive scientists bel ...
CHAMPION: Intelligent Hierarchical Reasoning Agents for Enhanced Decision Support
... 17]. Clearly this is an important requirement for the system that will facilitate the decision maker’s understanding of the reasoning process. The system has two locations where provenance information can be stored. The first is in the asserted individuals added to the graph. Reified individuals (i. ...
... 17]. Clearly this is an important requirement for the system that will facilitate the decision maker’s understanding of the reasoning process. The system has two locations where provenance information can be stored. The first is in the asserted individuals added to the graph. Reified individuals (i. ...
Agent Shell for the Development of Tutoring Systems for Expert
... The problem solving engines of our LTAS employ a general, divide-and-conquer, approach to problem solving, called problem-reduction/solution-synthesis, which is applicable in a wide range of domains [7], [11]. In this approach, which will be illustrated in the next section, a complex problem is succ ...
... The problem solving engines of our LTAS employ a general, divide-and-conquer, approach to problem solving, called problem-reduction/solution-synthesis, which is applicable in a wide range of domains [7], [11]. In this approach, which will be illustrated in the next section, a complex problem is succ ...
Ullman, 2004 - Brain and Language Lab
... phonology, whereas anterior/ventral inferior frontal cortex (BA 45/47) is more important for semantics (Fiez, 1997; Poldrack, Wagner et al., 1999). Their precise roles may be closely related to working memory (Buckner & Wheeler, 2001; Moscovitch, 1992). Indeed, neuroimaging studies show that VL-PFC ...
... phonology, whereas anterior/ventral inferior frontal cortex (BA 45/47) is more important for semantics (Fiez, 1997; Poldrack, Wagner et al., 1999). Their precise roles may be closely related to working memory (Buckner & Wheeler, 2001; Moscovitch, 1992). Indeed, neuroimaging studies show that VL-PFC ...
agents-StudentVersion - The Computer Science Department
... • The real world is not like that: things change, information is incomplete. Many (most?) interesting environments are dynamic • A reactive system is one that – maintains an ongoing interaction with its environment, – responds to changes that occur in it. ...
... • The real world is not like that: things change, information is incomplete. Many (most?) interesting environments are dynamic • A reactive system is one that – maintains an ongoing interaction with its environment, – responds to changes that occur in it. ...
Artificial Intelligence and Economic Theory
... sketched above. The main problem is that the method relies completely upon some external supervisor. In essence, by correcting parameters on the basis of some error function representing a measure of the distance between the' target' output y and the ANNs actual output y, the external supervisor tea ...
... sketched above. The main problem is that the method relies completely upon some external supervisor. In essence, by correcting parameters on the basis of some error function representing a measure of the distance between the' target' output y and the ANNs actual output y, the external supervisor tea ...
Reflection in Action: Meta-Reasoning for Goal
... to achieve a goal in its given environment), or proactive (i.e., when the agent is asked to operate in a new task environment). Secondly, adaptations can be either to the deliberative element in the agent architecture, or the reactive element, or both. Thirdly, adaptations to the deliberative elemen ...
... to achieve a goal in its given environment), or proactive (i.e., when the agent is asked to operate in a new task environment). Secondly, adaptations can be either to the deliberative element in the agent architecture, or the reactive element, or both. Thirdly, adaptations to the deliberative elemen ...
slides
... Dialogue Agent is trained on conversation sets Each conversation set is one “context unit” (CU) Agent database contains many CUs But not all of them have to be processed at all times Some of them could be deactivated when not needed (forgetting) and reactivated ...
... Dialogue Agent is trained on conversation sets Each conversation set is one “context unit” (CU) Agent database contains many CUs But not all of them have to be processed at all times Some of them could be deactivated when not needed (forgetting) and reactivated ...
INTELLIGENT AGENT PLANNING WITH QUASI
... The classical planning methods use a predicative logic representation for the states. For example, if a robotic agent has a plan of taking an apple off the table and putting it into a basket, a typical plan would use a predicate such as Apple(a) to describe this object. However, in a real-life situa ...
... The classical planning methods use a predicative logic representation for the states. For example, if a robotic agent has a plan of taking an apple off the table and putting it into a basket, a typical plan would use a predicate such as Apple(a) to describe this object. However, in a real-life situa ...
Agency Systems
... The classifications of strong and weak agency are not intended to be binding, but only represent a mechanism for typifying common features that may exist across agentbased systems. However, the attribution of these characteristics does serve to differentiate the agent paradigm from other paradigms, ...
... The classifications of strong and weak agency are not intended to be binding, but only represent a mechanism for typifying common features that may exist across agentbased systems. However, the attribution of these characteristics does serve to differentiate the agent paradigm from other paradigms, ...
Cognitive Primitives for Automated Learning
... indeterminate and fuzzy input and still achieve great degree of dependable solutions. Applications software are 'trained' on test cases devised and labeled by humans, scored so as to estimate its usefulness, and then tested on real-world cases. The results of these real-world cases are in-turn refle ...
... indeterminate and fuzzy input and still achieve great degree of dependable solutions. Applications software are 'trained' on test cases devised and labeled by humans, scored so as to estimate its usefulness, and then tested on real-world cases. The results of these real-world cases are in-turn refle ...
mul tiagent systems a modern approach to distributed artificial
... MAS. Careful coordination of the materials ensures the COherence ofthis book and contributed to the book's success. The book is divided into two parts. It reflects the state ofthe art in the field ofMAS, and treats basic themes (Part I) giving a clear and careful presentation ofthe key concepts, met ...
... MAS. Careful coordination of the materials ensures the COherence ofthis book and contributed to the book's success. The book is divided into two parts. It reflects the state ofthe art in the field ofMAS, and treats basic themes (Part I) giving a clear and careful presentation ofthe key concepts, met ...
EXPERT SYSTEM FOR DECISION-MAKING PROBLEM
... Typically, the problems to be solved are of the sort that would normally be tackled by a human “expert” – an economical or other professional, in most cases. Real experts in the problem domain are asked to provide "rules of thumb" on how they evaluate the problems, either explicitly with the aid of ...
... Typically, the problems to be solved are of the sort that would normally be tackled by a human “expert” – an economical or other professional, in most cases. Real experts in the problem domain are asked to provide "rules of thumb" on how they evaluate the problems, either explicitly with the aid of ...
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.