• Study Resource
  • Explore
    • Arts & Humanities
    • Business
    • Engineering & Technology
    • Foreign Language
    • History
    • Math
    • Science
    • Social Science

    Top subcategories

    • Advanced Math
    • Algebra
    • Basic Math
    • Calculus
    • Geometry
    • Linear Algebra
    • Pre-Algebra
    • Pre-Calculus
    • Statistics And Probability
    • Trigonometry
    • other →

    Top subcategories

    • Astronomy
    • Astrophysics
    • Biology
    • Chemistry
    • Earth Science
    • Environmental Science
    • Health Science
    • Physics
    • other →

    Top subcategories

    • Anthropology
    • Law
    • Political Science
    • Psychology
    • Sociology
    • other →

    Top subcategories

    • Accounting
    • Economics
    • Finance
    • Management
    • other →

    Top subcategories

    • Aerospace Engineering
    • Bioengineering
    • Chemical Engineering
    • Civil Engineering
    • Computer Science
    • Electrical Engineering
    • Industrial Engineering
    • Mechanical Engineering
    • Web Design
    • other →

    Top subcategories

    • Architecture
    • Communications
    • English
    • Gender Studies
    • Music
    • Performing Arts
    • Philosophy
    • Religious Studies
    • Writing
    • other →

    Top subcategories

    • Ancient History
    • European History
    • US History
    • World History
    • other →

    Top subcategories

    • Croatian
    • Czech
    • Finnish
    • Greek
    • Hindi
    • Japanese
    • Korean
    • Persian
    • Swedish
    • Turkish
    • other →
 
Profile Documents Logout
Upload
Tim Menzies, Windy Gambetta Artificial Intelligence Laboratory
Tim Menzies, Windy Gambetta Artificial Intelligence Laboratory

... model, then check that the known behaviour can be found amongst the possible behaviours. If not, then the model is faulty. Note that this algorithm is silent on the best internal form of the model. It assumes that issues such as (e.g.) the presence of loops, tautologies, redundancies, inconsistencie ...
Decision Support Systems
Decision Support Systems

... makers. However, decision making is frequently a shared process. Where a group may be involved in making the decision. When a decision-making group is supported electronically, the support is referred to as a group decision support system (GDSS). ...
Co-Designing Agents: A Vision
Co-Designing Agents: A Vision

... Answering “Why aren’t you doing/didn’t do x?” is related to answering “Why not?” (Chalupsky and Russ, 2002), but relates to acting rather than inferring beliefs. Answering “Why did/didn’t you do x?” opens the possibility of an answer like “Because . . . , but if I knew then what I do now, I would ha ...
CS 561: Artificial Intelligence
CS 561: Artificial Intelligence

... environment through sensors and acting upon that environment through its effectors to maximize progress towards its goals. ...
AI and Cinema - Does artificial insanity rule?
AI and Cinema - Does artificial insanity rule?

... explored by mainstream movies, in a context that allows us to ignore (or alternatively make explicit) questions of racism, sexism, etc. When an AI agent doesn’t act properly, we could easily dismiss this with a sense of superiority; with humans we cannot or should not. By treating a nearly human AI ...
Bounded Seed-AGI
Bounded Seed-AGI

... aim of looped-back adaptation and cognition. For detailed explanations of how exactly value, urgency, and priority are calculated in AERA, we refer interested readers to [1]. ...
AI and Agents
AI and Agents

... Cognitive Science and Psychology (testing/ predicting responses of human subjects) Cognitive Neuroscience (observing neurological data) ...
AI AND MACHINE LEARNING TECHNIQUES FOR MANAGING
AI AND MACHINE LEARNING TECHNIQUES FOR MANAGING

... unprecedented, unforeseen problems on the basis of even incomplete and imprecise information (Hatvany, 1983). ...
Using Distributed Data Mining and Distributed Artificial
Using Distributed Data Mining and Distributed Artificial

... a single dataset and then, some distributed learning approach must be used. DDM can deal with public datasets available on the Internet, corporate databases within an Intranet, environments for mobile computation, collections of distributed sensor data for monitoring, etc. Distributed Data Mining of ...
Natural and Artificial Systems: Compare, Model or - PUMA
Natural and Artificial Systems: Compare, Model or - PUMA

... enhance, our cognitive processes. EMT holds that the physical mechanisms of our thinking extends beyond our biological boundaries when a two-way relationship between cognitive and external systems exists – for example using a smart phone as an external memory store, or a notepad to work out a sum [1 ...
Mehran University of Engineering and Technology, Jamshoro
Mehran University of Engineering and Technology, Jamshoro

...  An Agent perceives and acts in an environment, has an architecture, and is implemented by an agent program.  An Ideal agent always chooses the action which maximizes its expected performance, given its percept sequence so far.  An Autonomous agent uses its own experience rather than built-in kno ...
CMPUT 650: Learning To Make Decisions
CMPUT 650: Learning To Make Decisions

... A hunt the Wumpus flash version: http://www.flashrolls.com/puzzlegames/Hunt-The-Wumpus-Flash-Game.htm ...
Pdf-preprint - Dipartimento di Informatica
Pdf-preprint - Dipartimento di Informatica

... the sufficiency, from an epistemological perspective, of a weak equivalence between cognitive processes and AI procedures and propose that, from an explanatory point of view, the relation between “natural mind” and “artificial software” can be based purely on a macroscopic equivalence of the functio ...
Using Complexity Theory Methods for Sociological Theory
Using Complexity Theory Methods for Sociological Theory

... of CT have roots in the development of traditional social system theories in sociology. The notion of analyzing the society and social phenomena as social systems has traditionally been dominant within sociology, beginning with the classics in sociology such as Marx, Durkheim, Compte, Pareto and Web ...
Preface - Beck-Shop
Preface - Beck-Shop

... achieves and/or maintains given goals and prove some new results about the complexity of the agent design problem under various assumptions. They look at optimistic agent design, where the agent is only required to achieve/maintain its goals for some execution of the specified environment. They also ...
CV - Olivier Georgeon
CV - Olivier Georgeon

... interaction. A TBR system incrementally discovers, records, hierarchically abstracts, and reuses interesting episodes of interaction at different levels of abstraction. ...
Cognitive Requirements for Agent
Cognitive Requirements for Agent

... of the environment on a constructivist (high learner control) to instructivist (high program/agent control) continuum. The second dimension entails managing feedback, and several issues need to be considered: type, timing, amount, explicitness, and learner control of agent feedback. Third, agent vs ...
Dimensions of Interaction
Dimensions of Interaction

From: AAAI Technical Report FS-0 -0 . Compilation copyright © 200
From: AAAI Technical Report FS-0 -0 . Compilation copyright © 200

... Copyright © 2002, AAAI Press The American Association for Artificial Intelligence 445 Burgess Drive Menlo Park, California 94025 ...
Slides
Slides

... General Performance, General Distribution  Artificial General Intelligence must focus on general tasks.  We can construct a general set of tasks by aggregating several problems which humans face everyday.  Arbitrary approach (how many of these, how many of those, ...)  Makes it difficult to kno ...
emerging the emergence sociology
emerging the emergence sociology

... It is quite difficult to analyze the dynamical behavior of each network specified by w, in general. It is usually in the nature of social system, the value of n is large, and we sometimes wish to understand the macroscopic behavior of the networks which have some statistical properties of connection ...
SPECTR1
SPECTR1

... formula to compute thousands of similar cases. When this occurs the computer program operates as an algorithm repeating the same series of computational steps on input data for each case processed. Deterministic programs are not very interesting from the modeling perspective, but account for most ap ...
IDA: A Cognitive Agent Architecture
IDA: A Cognitive Agent Architecture

... Franklin and Dasgupta, 1998; Zhang et al, 1998). This paper briefly describes the architecture of one such agent. By an autonomous agent (Franklin and Graesser 1997) we mean a system situated in, and part of, an environment, which senses that environment, and acts on it, over time, in pursuit of its ...
A New Platform for Developing Virtual Organizations of Agents
A New Platform for Developing Virtual Organizations of Agents

... principal categories: those that simply support the creation and interaction of agents, and those that permit the creation of virtual organizations with such key concepts as norms and roles. We will first present those platforms that do not incorporate organizational aspects. The FIPA-OS (Poslad et. ...
Reports of the AAAI 2011 Fall Symposia
Reports of the AAAI 2011 Fall Symposia

< 1 ... 14 15 16 17 18 19 20 21 22 ... 35 >

Agent-based model

An agent-based model (ABM) is one of a class of computational models for simulating the actions and interactions of autonomous agents (both individual or collective entities such as organizations or groups) with a view to assessing their effects on the system as a whole. It combines elements of game theory, complex systems, emergence, computational sociology, multi-agent systems, and evolutionary programming. Monte Carlo Methods are used to introduce randomness. Particularly within ecology, ABMs are also called individual-based models (IBMs), and individuals within IBMs may be simpler than fully autonomous agents within ABMs. A review of recent literature on individual-based models, agent-based models, and multiagent systems shows that ABMs are used on non-computing related scientific domains including biology, ecology and social science. Agent-based modeling is related to, but distinct from, the concept of multi-agent systems or multi-agent simulation in that the goal of ABM is to search for explanatory insight into the collective behavior of agents obeying simple rules, typically in natural systems, rather than in designing agents or solving specific practical or engineering problems.Agent-based models are a kind of microscale model that simulate the simultaneous operations and interactions of multiple agents in an attempt to re-create and predict the appearance of complex phenomena. The process is one of emergence from the lower (micro) level of systems to a higher (macro) level. As such, a key notion is that simple behavioral rules generate complex behavior. This principle, known as K.I.S.S. (""Keep it simple, stupid"") is extensively adopted in the modeling community. Another central tenet is that the whole is greater than the sum of the parts. Individual agents are typically characterized as boundedly rational, presumed to be acting in what they perceive as their own interests, such as reproduction, economic benefit, or social status, using heuristics or simple decision-making rules. ABM agents may experience ""learning"", adaptation, and reproduction.Most agent-based models are composed of: (1) numerous agents specified at various scales (typically referred to as agent-granularity); (2) decision-making heuristics; (3) learning rules or adaptive processes; (4) an interaction topology; and (5) a non-agent environment. ABMs are typically implemented as computer simulations, either as custom software, or via ABM toolkits, and this software can be then used to test how changes in individual behaviors will affect the system's emerging overall behavior.
  • studyres.com © 2025
  • DMCA
  • Privacy
  • Terms
  • Report