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Agent definitions - Computer Science
Agent definitions - Computer Science

... • The complexity of such a system or the fact that we can not know or predict the internal structure of all components seems to imply that we must rely on animistic, intentional explanation of system functioning and behaviour. • We thus come again to the idea presented in the beginning: try to appl ...
session02
session02

... • Agents have social ability, that is, they communicate with the user, the system, and other agents as required • Agents may also cooperate with other agents to carry out more complex tasks than they themselves can handle • Agents may migrate from one system to another to access remote resources or ...
INTELLIGENT AGENT PLANNING WITH QUASI
INTELLIGENT AGENT PLANNING WITH QUASI

... In order to address the issue of reactive actions, we propose that besides recognizing the preconditions of an action, classification can be used to directly map a state to an action. A training dataset can be used to choose the appropriate action in a state instead of a conditional planning method. ...
The Learning Intelligent Distribution Agent (LIDA)
The Learning Intelligent Distribution Agent (LIDA)

... B. LIDA’s Modules and Cognitive Cycle LIDA’s conceptual model comprises a number of modules that serve as a functional taxonomy for mental processes (Fig. 1). The modules provide descriptions of functionally related cognitive processes, and imply neither anatomic modularity in the brain, nor a stron ...
Multiple Workspaces as an Architecture for Cognition
Multiple Workspaces as an Architecture for Cognition

... They are both simple to comprehend and allow the construction of effective systems. In ACT-R [1] John Andersen and colleagues have taken some of the elements of production systems and used them to produce models of aspects of human cognition that produce testable predictions. In ACT-R productions no ...
An Overview of the Assisted Cognition Project
An Overview of the Assisted Cognition Project

... seven stage theory describes the typical progress of the disease. In stage 1, the disease has begun but is asymptomatic. In early Alzheimer’s, stages 2–3, patients exhibit forgetfulness, easily become lost, have difficulty with word and name recognition, misplace objects, etc. In the middle stages, ...
Challenges in Computational Modeling of Affective Processes
Challenges in Computational Modeling of Affective Processes

... computational model is embedded in an agent and the agent can be embedded in a task context, enabling the model to produce for humans meaningful output. For example, an intelligent virtual character can express emotions while it negotiates with a human [9]. From a theoretical perspective this means ...
pdf file
pdf file

... human is guided only at the level of his or her behaviour and not at the level of the underlying cognitive states causing the behaviour. Such a situation might lead to suggesting the human to suppress behaviour that is entailed by his or her internal cognitive states, without taking into account the ...
JRobin - LES - PUC-Rio
JRobin - LES - PUC-Rio

... backjumping for disjunctive rule and finite domain labeling search ...
CS 561a: Introduction to Artificial Intelligence
CS 561a: Introduction to Artificial Intelligence

... • Agents are autonomous, that is they act on behalf of the user • Agents contain some level of intelligence, from fixed rules to learning engines that allow them to adapt to changes in the environment • Agents don't only act reactively, but sometimes also proactively • Agents have social ability, th ...
CS 561a: Introduction to Artificial Intelligence
CS 561a: Introduction to Artificial Intelligence

... • Agents have social ability, that is, they communicate with the user, the system, and other agents as required • Agents may also cooperate with other agents to carry out more complex tasks than they themselves can handle • Agents may migrate from one system to another to access remote resources or ...
Word - Semiosis Evolution Energy
Word - Semiosis Evolution Energy

... 2. Whereas Peirce does not pick the distinction of syntagmatic and paradigmatic regularities – especially with respect to textual units above the level of argumentative structures – as a central topic of his sign philosophy, this distinction, which parallels the distinction of text system and langua ...
ID2209 Distributed Artificial Intelligence and Intelligent Agents
ID2209 Distributed Artificial Intelligence and Intelligent Agents

... We assume that most of devices in your home (such as refrigerator, washing machine, dish-washing machine, even wardrobe etc.) are software assistants (at least they are represented by software assistants). You are also represented by your software assistant. Imagine that you told your software assis ...
A Comparative Study of Soft Computing Methodologies in
A Comparative Study of Soft Computing Methodologies in

... The mapping properties of artificial neural networks have been analyzed by many researchers. Hornik [1], and Funahashi [2] have shown that as long as the hidden layer comprises sufficient number of nonlinear neurons, a function can be realized with a desired degree of accuracy. This proof is followe ...
Agent Chameleons: Virtual Agents Real Intelligence
Agent Chameleons: Virtual Agents Real Intelligence

... dependent matters. The Social Beliefs are developed based on social interaction between the agent and other socially capable entities. These Beliefs are augmented by information from the Environmental and Reactive Layers. • Commitment Rules – The Commitment Rules are a core part of the Deliberative ...
Intelligent Systems: Perspectives and Research Challenges
Intelligent Systems: Perspectives and Research Challenges

... inspired mainly  by  engineering and  computational  considerations  and some  by  cognitive  science  in  its  attempt  to  model  psychological  data.  Some  were  even  influenced by ideas about how various brain regions function. Parallel operation  is  assumed  in  many  of  these  architectur ...
Note 1: introduction
Note 1: introduction

... • Thinking humanly – cognitive modeling • Understand the workings of human minds – Once we have a theory of the mind, we can express the theory as a computer program ...
System Intelligence, Knowledge Systems and Darwin
System Intelligence, Knowledge Systems and Darwin

... My aim is to dig deeper into some essentials of Systems Intelligence (Saarinen et al. 2004) by using tools of System Analysis and applying an evolutionary model of knowledge generation. I hope to find explanations for some Systems Intelligence fundaments and answers to the question: Why is Systems I ...
2014 IEEE International Conference on Systems, Man
2014 IEEE International Conference on Systems, Man

... San Diego, California The 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC2014) will be held at the luxurious Paradise Point Resort and Spa, 1404 Vacation Road, San Diego, located 15 minutes north on a 44 acre private island of Mission Bay. Paradise Point features comfortable ...
INTCare: A Knowledge Discovery based Intelligent Decision
INTCare: A Knowledge Discovery based Intelligent Decision

... 2.1 Decision Support Systems and Intensive Care In the beginning of the 80s, several expert systems were developed for medicine, such as MYCIN (Buchanan et al., 1984), CASNET (Kulikowski et al., 1982) and CADUCEUS (Pople 1985), just to name a few. A decade later, in the 90s, the common knowledge was ...
AUML Protocols and Code Generation in the
AUML Protocols and Code Generation in the

... Prometheus methodology describes how this is done by grouping roles, considering coupling and cohesion, using a data coupling and an agent acquaintance diagram, etc. Prometheus consists of three phases (depicted in figure 1): • System specification: in which the goals of the system are identified, t ...
Jean Piaget (1896
Jean Piaget (1896

... increases in sophistication with development, moving from a few natural reflexes such as crying and sucking to highly complex mental activities  Piaget's theory supposes that people develop schemas (conceptual models) by either assimilating or accommodating new information ...
stairs 2012 - Shiwali Mohan
stairs 2012 - Shiwali Mohan

... set of actions. Thus, action selection at the second level of the action selection hierarchy is quantitative. Additionally, whenever a new state is encountered, the action optimal for the nearest similar state is selected. We find the nearest similar state as follows. A search is made into the state ...
Putting some (artificial) life into models of musical creativity
Putting some (artificial) life into models of musical creativity

... the individuals singing those songs, and hence to more copies of versions of those songs in the next generation. This artificial evolutionary process can lead to more complex or interesting pieces of music if allowed to go on long enough. In models of this type, music production is intrinsic to eac ...
Intelligent Agents
Intelligent Agents

... can communicate by message passing. Despite these similarities, there are significant differences between agents and objects. An object may be said to exhibit autonomy over its state (by defining its instance variables as private) but it does not exhibit control over its behavior. The designers of a ...
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Cognitive model

A cognitive model is an approximation to animal cognitive processes (predominantly human) for the purposes of comprehension and prediction. Cognitive models can be developed within or without a cognitive architecture, though the two are not always easily distinguishable.In contrast to cognitive architectures, cognitive models tend to be focused on a single cognitive phenomenon or process (e.g., list learning), how two or more processes interact (e.g., visual search and decision making), or to make behavioral predictions for a specific task or tool (e.g., how instituting a new software package will affect productivity). Cognitive architectures tend to be focused on the structural properties of the modeled system, and help constrain the development of cognitive models within the architecture. Likewise, model development helps to inform limitations and shortcomings of the architecture. Some of the most popular architectures for cognitive modeling include ACT-R and Soar.
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