essentials of expert system and its applications
... university of Stanford. In 1950, the AI field evolved into a machine which performs intelligently if an interrogate using remote terminals cannot distinguish its responses from those of humans which is tuning test. Thus resulting in general problem solving method. In 1960, AI is considered to be wel ...
... university of Stanford. In 1950, the AI field evolved into a machine which performs intelligently if an interrogate using remote terminals cannot distinguish its responses from those of humans which is tuning test. Thus resulting in general problem solving method. In 1960, AI is considered to be wel ...
Exploring the Complex Interplay between AI and Consciousness
... would be easily integrated into old. Several tasks could be learned concurrently with transfer of knowledge to new tasks. It is important to acknowledge that not all artificial agents require consciousness to achieve their goals. In fact agents involved in relatively simple tasks in restricted domai ...
... would be easily integrated into old. Several tasks could be learned concurrently with transfer of knowledge to new tasks. It is important to acknowledge that not all artificial agents require consciousness to achieve their goals. In fact agents involved in relatively simple tasks in restricted domai ...
1. The Concept of Artificial Intelligence Artificial Intelligence (AI) is a
... finding solutions to complex problems in a more human-like fashion. This generally involves borrowing characteristics from human intelligence, and applying them as algorithms in a computer friendly way. A more or less flexible or efficient approach can be taken depending on the requirements establis ...
... finding solutions to complex problems in a more human-like fashion. This generally involves borrowing characteristics from human intelligence, and applying them as algorithms in a computer friendly way. A more or less flexible or efficient approach can be taken depending on the requirements establis ...
Artificial Intelligence
... similarities between two systems to support the conclusion that some further similarity exists. In general (but not always), such arguments belong in the category of inductive reasoning, since their conclusions do not follow with certainty but are only supported with varying degrees of strength. ...
... similarities between two systems to support the conclusion that some further similarity exists. In general (but not always), such arguments belong in the category of inductive reasoning, since their conclusions do not follow with certainty but are only supported with varying degrees of strength. ...
Computational Models of Emotion and Cognition
... Appraisal theory is dominant in the community of computational emotional modeling, although other schools of thought have also made an impact in that arena. The theory was developed as a means to predict individual human emotions given particular situations (Arnold, 1960; Lazarus, 1966; Scherer, 199 ...
... Appraisal theory is dominant in the community of computational emotional modeling, although other schools of thought have also made an impact in that arena. The theory was developed as a means to predict individual human emotions given particular situations (Arnold, 1960; Lazarus, 1966; Scherer, 199 ...
CS 460: Artificial Intelligence
... should eventually succeed. It is a race, but both racers seem to be walking. [John McCarthy] CS 460, Lecture 1 ...
... should eventually succeed. It is a race, but both racers seem to be walking. [John McCarthy] CS 460, Lecture 1 ...
CS 561a: Introduction to Artificial Intelligence
... should eventually succeed. It is a race, but both racers seem to be walking. [John McCarthy] CS 460, Lecture 1 ...
... should eventually succeed. It is a race, but both racers seem to be walking. [John McCarthy] CS 460, Lecture 1 ...
session01
... should eventually succeed. It is a race, but both racers seem to be walking. [John McCarthy] CS 460, Lecture 1 ...
... should eventually succeed. It is a race, but both racers seem to be walking. [John McCarthy] CS 460, Lecture 1 ...
session01
... should eventually succeed. It is a race, but both racers seem to be walking. [John McCarthy] CS 460, Lecture 1 ...
... should eventually succeed. It is a race, but both racers seem to be walking. [John McCarthy] CS 460, Lecture 1 ...
Production Rules as a Representation for a Knowledge
... Instead of writing rules whose premise would be a disjtmction of clauses, we write a separate rule for each clause. The action part indicates one or more conclusions which can be drawn i f the premises are satisfied; hence the rules are (currently) purely inferential in chancter. It is intended that ...
... Instead of writing rules whose premise would be a disjtmction of clauses, we write a separate rule for each clause. The action part indicates one or more conclusions which can be drawn i f the premises are satisfied; hence the rules are (currently) purely inferential in chancter. It is intended that ...
Adding Consciousness to Cognitive Architectures
... 14.1 Example of a RCS hierarchy from [1], in which there can be appreciated the different resolution levels . . . . . . . . . . . 14.2 Functional structure of a RCS node . . . . . . . . . . . . . . 14.3 World Modelling and Value Judgement processes (from [1]) . 14.4 Internal structure of Behaviour Ge ...
... 14.1 Example of a RCS hierarchy from [1], in which there can be appreciated the different resolution levels . . . . . . . . . . . 14.2 Functional structure of a RCS node . . . . . . . . . . . . . . 14.3 World Modelling and Value Judgement processes (from [1]) . 14.4 Internal structure of Behaviour Ge ...
KBS88.pdf
... aspects of a model of rationality corresponds to a distinction one can make between two different aspects of an expert system. First, there is the 'domain' in which the expert system is to solve problems. For example, the domain of an expert system may be electronics, or internal medicine. Secondly, ...
... aspects of a model of rationality corresponds to a distinction one can make between two different aspects of an expert system. First, there is the 'domain' in which the expert system is to solve problems. For example, the domain of an expert system may be electronics, or internal medicine. Secondly, ...
hybrid expert system agents - Universitatea"Petru Maior"
... diagnosis system is proposed for difficult problems solving, like the diagnoses of combinations of illnesses (patients that suffer from combinations of illnesses). In the papers [5, 6] are analyzed different aspects related with a novel hybrid diagnosis system. The novelty consists in the diagnosis ...
... diagnosis system is proposed for difficult problems solving, like the diagnoses of combinations of illnesses (patients that suffer from combinations of illnesses). In the papers [5, 6] are analyzed different aspects related with a novel hybrid diagnosis system. The novelty consists in the diagnosis ...
Commonsense Reasoning by Integrating Simulation and Logic
... real-world. That is, our emphasis is not on capturing commonly known factual knowledge (“Who is the Queen of England?”), but to create systems with real-world ‘know-how’ (“How can I safely rescue this person?”). In lieu of a rigorous definition of commonsense intelligence, we make use of benchmark p ...
... real-world. That is, our emphasis is not on capturing commonly known factual knowledge (“Who is the Queen of England?”), but to create systems with real-world ‘know-how’ (“How can I safely rescue this person?”). In lieu of a rigorous definition of commonsense intelligence, we make use of benchmark p ...
How to Reason by HeaRT in a Semantic Knowledge-Based Wiki
... that supports inference with production rules. Several modes for modularized rule bases, suitable for the distributed rule bases present in a wiki, are considered. Embedding the rule engine enables strong reasoning and allows to run production rules over semantic knowledge bases. In the paper, we de ...
... that supports inference with production rules. Several modes for modularized rule bases, suitable for the distributed rule bases present in a wiki, are considered. Embedding the rule engine enables strong reasoning and allows to run production rules over semantic knowledge bases. In the paper, we de ...
CS6659-ARTIFICIAL INTELLIGENCE
... In optimization problems, the aim is to find the best state according to an objective function the optimization problem is then: Find values of the variables that minimize or maximize the objective function while satisfying the constraints. 31. What is Hill-climbing search? The Hill-climbing algorit ...
... In optimization problems, the aim is to find the best state according to an objective function the optimization problem is then: Find values of the variables that minimize or maximize the objective function while satisfying the constraints. 31. What is Hill-climbing search? The Hill-climbing algorit ...
Cognitive Robotics - Knowledge
... as in robotic soccer [21], where little is known beyond their position on a soccer field, to the very complex, involving knowledge about the actual shape of the objects [60, 71]. Likewise, knowledge about actions can be as simple as taking an action to be a discrete change of position from A to B, o ...
... as in robotic soccer [21], where little is known beyond their position on a soccer field, to the very complex, involving knowledge about the actual shape of the objects [60, 71]. Likewise, knowledge about actions can be as simple as taking an action to be a discrete change of position from A to B, o ...
The role of artificial intelligence techniques in training
... explanation, they adapt this explanation to the explainee. They especially vary the granularity of the explanation. If the explainer believes that the explainee knows some parts of the explanation, these parts may be presented very briefly or even skipped. Conversely, for the newer, more difficult, ...
... explanation, they adapt this explanation to the explainee. They especially vary the granularity of the explanation. If the explainer believes that the explainee knows some parts of the explanation, these parts may be presented very briefly or even skipped. Conversely, for the newer, more difficult, ...
Karlsruhe Text - Tecfa
... explanation, they adapt this explanation to the explainee. They especially vary the granularity of the explanation. If the explainer believes that the explainee knows some parts of the explanation, these parts may be presented very briefly or even skipped. Conversely, for the newer, more difficult, ...
... explanation, they adapt this explanation to the explainee. They especially vary the granularity of the explanation. If the explainer believes that the explainee knows some parts of the explanation, these parts may be presented very briefly or even skipped. Conversely, for the newer, more difficult, ...
Automated Agent Decomposition for Classical Planning
... smaller lower case letters label the locations. and Rosenschein (1993) propose a mechanism where each agent votes for or against the next joint action in a multiagent plan based on whether local constraints are satisfied by a proposed state transition. Brafman et al (2009) apply constraint satisfact ...
... smaller lower case letters label the locations. and Rosenschein (1993) propose a mechanism where each agent votes for or against the next joint action in a multiagent plan based on whether local constraints are satisfied by a proposed state transition. Brafman et al (2009) apply constraint satisfact ...
session02
... • Manage the explosive growth of information. • Manipulate or collate information from many distributed sources. • Information agents can be mobile or static. ...
... • Manage the explosive growth of information. • Manipulate or collate information from many distributed sources. • Information agents can be mobile or static. ...
An Equal Excess Negotiation Algorithm for Coalition
... that the tasks that PACT allocates are mostly identical to those selected by the utilitarian solution. Our second set of experiments test the scalability of the PACT algorithm. We first test PACT scalability in terms of the number of agents and tasks for various agent/task distributions. Our results ...
... that the tasks that PACT allocates are mostly identical to those selected by the utilitarian solution. Our second set of experiments test the scalability of the PACT algorithm. We first test PACT scalability in terms of the number of agents and tasks for various agent/task distributions. Our results ...
Influence-Based Abstraction for Multiagent Systems Please share
... POSGs can be decomposed into local models. We formalize the interface between such local models as the influence agents can exert on one another; and we prove that this interface is sufficient for decoupling them. The resulting influence-based abstraction substantially generalizes previous work on e ...
... POSGs can be decomposed into local models. We formalize the interface between such local models as the influence agents can exert on one another; and we prove that this interface is sufficient for decoupling them. The resulting influence-based abstraction substantially generalizes previous work on e ...
Massively Parallel Artificial Intelligence
... and efficiency between the host and parallel processing modules have to be designed carefully to alleviate the problem. In addition, the introduction of the process ing capability located in an intermediate level between the host and parallel processing modules may be very effective for this proble ...
... and efficiency between the host and parallel processing modules have to be designed carefully to alleviate the problem. In addition, the introduction of the process ing capability located in an intermediate level between the host and parallel processing modules may be very effective for this proble ...
Intelligent Agents. - Home ANU
... There are several basic agent architectures: reflex, reflex with state, goal-based, utility-based Learning can be added to any basic architecture and is indeed essential for satisfactory performance in many applications. Rationality requires a learning component – it is necessary to know as much abo ...
... There are several basic agent architectures: reflex, reflex with state, goal-based, utility-based Learning can be added to any basic architecture and is indeed essential for satisfactory performance in many applications. Rationality requires a learning component – it is necessary to know as much abo ...
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.