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Bounded Seed-AGI
Bounded Seed-AGI

... of fine-grained jobs and are thus reusable and shared system-wide, collectively implementing functions that span across the entire scope of the system’s operation in its environment. High-level processes (like planning and learning) influence each other: For example, learning better models and seque ...
Four approaches to defining AI systems Cognitive science Rational
Four approaches to defining AI systems Cognitive science Rational

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Goal: Strengthen interdisciplinary research and
Goal: Strengthen interdisciplinary research and

... Vision as in the Strategic Plan [2003] • The faculty will be preeminent in creating and disseminating new knowledge on computing and communication. The department will prepare students to be leaders in computer science and its applications. Multidisciplinary activities that strengthen the impact of ...
Jensen.Gitelman.SSDAAR2.Poster.2003
Jensen.Gitelman.SSDAAR2.Poster.2003

... NP-hard problem. Although restriction to decomposable models only requires a single triangulation. (Deshpande et al., 2001). An extension of this method is possible by first using HUGIN or another package first to find a set of candidate models (that is, to perform the structural learning), and then ...
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... In reinforcement learning, there is a tradeoff between spending time acting in the environment and spending time planning what actions are best. Model-free methods take one extreme on this question— the agent updates only the state most recently visited. On the other end of the spectrum lie classica ...
An Investigation into the Role of Cortical Synaptic Depression in
An Investigation into the Role of Cortical Synaptic Depression in

... Explanations for forward masking have also been sought in terms of lateral or forward inhibition. However, it has been shown that masking continues to exist even in the presence of a GABA A antagonist and therefore even if inhibitory inputs have some part to play they cannot provide a full account ( ...
Cooperative Intelligent Agents
Cooperative Intelligent Agents

... a) a written paper of about 10 pages b) an oral presentation - an one-page outline of the presentation The paper will contain theoretical considerations on the selected topic and COMPULSORY sections regarding: 1. existing or possible applications of the selected topic 2. advantages and disadvantages ...
A Model for Design of Societies of Cooperative Agents
A Model for Design of Societies of Cooperative Agents

... Modularity of system. It is easier to create and to maintain a set of independent modules rather than a big one. Efficiency. Not all the knowledge is used in all tasks at the time. Modulating it you can focus the efforts of the problem solving system through more adequate paths. Fast computationa ...
PPT
PPT

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Planarian Studies by Artificial Intelligence
Planarian Studies by Artificial Intelligence

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Macroeconomic Analysis and Parametric Control Based on
Macroeconomic Analysis and Parametric Control Based on

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Models and Selection Criteria for Regression and Classification x, y

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lecture1-457

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chapter1

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Multi Agent System & Holonic Manufacturing System
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... the 2nd International Joint Conference on Autonomous Agents and MultiAgent Systems (AAMAS'03), 2003. J. Casper, M. Micire, and R. R. Murphy. Issues in intelligent robots for search and rescue. In Proceedings SPIE ...
Talk3.26.07V02 - Purdue University
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Road Map - Computer Science Department

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RMASBench: a Benchmarking System for Multi
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... and MaxSum, two state of the art DCOP solution techniques. The rational behind this choice is twofold: i) the DCOP framework allows to efficiently solve complex problems by exploiting domain structure and ii) there are a rich wealth of solution techniques for DCOPs (both exact and approximate) that ...
Modeling the production of VCV sequences via the inversion
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... We call static forward model a functional model of the relations between the motor commands sent to the tongue muscles and the spectral characteristics of the acoustic speech signal. It was elaborated using a 2D biomechanical model of the tongue. 2.1. The 2D biomechanical tongue model [8, 9] Elastic ...
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... Given this problem, it is under debate among several authors whether adequate alternative notions of representational content exist for such an embodied agent’s internal states. Some authors claim that for at least part of the internal states it makes no sense to consider them as conceptual or as ha ...
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The Economic Optimization of Mining Support Scheme Based on

... cases, the goal of any support system is to achieve safety production and economical cost. The support needed to accomplish this objective depends on the mechanical computing and economical optimization. From the mechanical view, many researchers have done many works range from the rock properties, ...
Artificial Intelligence Support for Scientific Model
Artificial Intelligence Support for Scientific Model

... a high-level domainspecific modeling language, a library of physics equations and experimental datasets, and a suite of data display facilities. 1. Introduction and Motivation: Software support for scientific model-building Model-buildingis an integral part of the scientific enterprise. Scientists s ...
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Agent-based model in biology

Agent-based models have many applications in biology, primarily due to the characteristics of the modeling method. Agent-based modeling is a rule-based, computational modeling methodology that focuses on rules and interactions among the individual components or the agents of the system. The goal of this modeling method is to generate populations of the system components of interest and simulate their interactions in a virtual world. Agent-based models start with rules for behavior and seek to reconstruct, through computational instantiation of those behavioral rules, the observed patterns of behavior. Several of the characteristics of agent-based models important to biological studies include: Modular structure: The behavior of an agent-based model is defined by the rules of its agents. Existing agent rules can be modified or new agents can be added without having to modify the entire model. Emergent properties: Through the use of the individual agents that interact locally with rules of behavior, agent-based models result in a synergy that leads to a higher level whole with much more intricate behavior than those of each individual agent. Abstraction: Either by excluding non-essential details or when details are not available, agent-based models can be constructed in the absence of complete knowledge of the system under study. This allows the model to be as simple and verifiable as possible. Stochasticity: Biological systems exhibit behavior that appears to be random. The probability of a particular behavior can be determined for a system as a whole and then be translated into rules for the individual agents.Before the agent-based model can be developed, one must choose the appropriate software or modeling toolkit to be used. Madey and Nikolai provide an extensive list of toolkits in their paper ""Tools of the Trade: A Survey of Various Agent Based Modeling Platforms"". The paper seeks to provide users with a method of choosing a suitable toolkit by examining five characteristics across the spectrum of toolkits: the programming language required to create the model, the required operating system, availability of user support, the software license type, and the intended toolkit domain. Some of the more commonly used toolkits include Swarm, NetLogo, RePast, and Mason. Listed below are summaries of several articles describing agent-based models that have been employed in biological studies. The summaries will provide a description of the problem space, an overview of the agent-based model and the agents involved, and a brief discussion of the model results.
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