• 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
Recent advances in computational models of natural argument
Recent advances in computational models of natural argument

... readers of Comment pages in newspapers. Sillince and Minors 69 provide yet another argument representation language, focusing on handling field-dependent argument strength, providing what Krause et al.11 would regard as a data dictionary for evaluation. In some cases, argument-based knowledge engine ...
Intelligent Virtual Environments - A State-of-the
Intelligent Virtual Environments - A State-of-the

... limited battery time that often frustrate researchers in robotics. With less effort required to develop basic control architectures – often adapted directly from robotics – it becomes possible with intelligent virtual agents, or synthetic characters, to investigate the modelling of emotion and the b ...
A comprehensive survey of multi
A comprehensive survey of multi

... This paper provides a detailed discussion of MARL techniques for fully cooperative, fully competitive, and mixed (neither cooperative nor competitive) tasks. The focus is placed on autonomous multiple agents learning how to solve dynamic tasks online, using learning techniques with roots in dynamic ...
The Behavior-Oriented Design of Modular Agent Intelligence
The Behavior-Oriented Design of Modular Agent Intelligence

... 2. reactive planning, the ordering of expressed actions via carefully specified program structures, and 3. (optionally) deliberative planning, which may inform or create new reactive plans, or, in principle, even learn new behaviors. In this section I will discuss these systems and their history in ...
Solving Complex Logistics Problems with Multi
Solving Complex Logistics Problems with Multi

... problem-solving features, with the collective effort of multiple problem solvers to combine their knowledge, information and capabilities in order to figure out solutions to quality problems, each of which could not be solved alone. 4. Distributed problem solving module (DPSM) Fig. 1. Infrastructure ...
A Future for Agent Programming
A Future for Agent Programming

... higher than 10%. However even allowing for these factors, it seems hard to argue that BDI agents are having a significant impact in application development. In this paper I explore the reasons for the apparent lack of interest in agent programming in the broader AI research community and developers ...
Artificial Emotion Simulation Techniques for Intelligent Virtual
Artificial Emotion Simulation Techniques for Intelligent Virtual

... another aspect of human intelligence. Research in human emotion has provided insight into how emotions influence human cognitive structures and processes, such as perception, memory management, planning, reasoning and behavior. This information also provides new ideas to researchers in the fields of ...
egpai 2016 - ECAI 2016
egpai 2016 - ECAI 2016

... The intuition is to encourage people in the AI community to evaluate new types of heuristics and algorithms in individual and collective scenarios using different communication and interaction protocols. This will hopefully pave the way towards a rigorous, formal and unified testing framework for ge ...
Modeling Opponent Decision in Repeated One
Modeling Opponent Decision in Repeated One

... In many negotiation and bargaining scenarios, a particular agent may need to interact repeatedly with another agent. Typically, these interactions take place under incomplete information, i.e., an agent does not know exactly which offers may be acceptable to its opponent or what other outside option ...
The SCHOLAR Legacy: A New Look at the Affordances of Semantic
The SCHOLAR Legacy: A New Look at the Affordances of Semantic

... to the design and construction of intelligent tutoring systems, especially generalpurpose systems such as GIFT. First, it is notable that semantic networks provide an efficient way of storing and retrieving information [Collins & Quillian, 1969]. Because nodes inherit the properties of the nodes the ...
Distributed multi-agent probabilistic reasoning with Bayesian networks
Distributed multi-agent probabilistic reasoning with Bayesian networks

... relevant tests as well: sputum test (ρ) and biopsy (o). Lab reports describe their impression upon τ and ι based on the results of the test(s). The above fictitious example involves three agents: a clinical doctor, a radiologist, and a biologist. Diagnosis of a patient with dyspnoea is their common ...
Intelligence Without Reason
Intelligence Without Reason

... today. The study of that substrate may well provide constraints on how higher level thought in humans could be organized. Recently there has been a movement to study intel­ ligence from the bottom up, concentrating on physical systems (e.g., mobile robots), situated in the world, au­ tonomously carr ...
CS 445 / 645 Introduction to Computer Graphics
CS 445 / 645 Introduction to Computer Graphics

... An agent can be a simple reflex agent, or an agent which knows its state, has a goal, or chooses the best sequence of states to reach its goal. ...
A bibliography for the development of an intelligent mathematical
A bibliography for the development of an intelligent mathematical

... way to divide the project's scope is: formulation, analysis and discourse. There are, however, interdependent components that pertain to model management, software engineering, learning models, and other elements taken from a variety of disciplines. ...
Decision Support Systems - University of Pittsburgh
Decision Support Systems - University of Pittsburgh

... There is a substantial amount of empirical evidence that human intuitive judgment and decision making can be far from optimal, and it deteriorates even further with complexity and stress. Because in many situations the quality of decisions is important, aiding the deficiencies of human judgment and ...
Excuse me, I need better AI! Employing Collaborative Diffusion to
Excuse me, I need better AI! Employing Collaborative Diffusion to

... to build collaborative agents and introduces the Collaborative Diffusion framework addressing these issues. A quick survey of game developer resources indicates a rich presence of AI related topics. Numerous books, e.g., AI for Game Developers [4], and websites, e.g., gameai.com, are dedicated to wh ...
preprint
preprint

... Over the last decade, Bayesian modeling has become more and more important as a modeling framework in cognitive science. Many of such Bayesian models postulate that cognitive processes perform some form of Bayesian inference.1 Examples of such models can be found in several different cognitive domai ...
Systems Engineering and Architecting for Intelligent Autonomous
Systems Engineering and Architecting for Intelligent Autonomous

... specifying how those components are actually realized in hardware and/or software. The logical architecture components are subsequently mapped onto software elements, which are deployed on hardware computation units. The computation and communication systems may further be partitioned in time and sp ...
Quasi-realistic climate models
Quasi-realistic climate models

... Models for reduction of complex systems • identification of significant, small subsystems and key processes • often derived through scale analysis (Taylor expansion with some characteristic numbers) ...
AII and Heterogeneous Design with - ICAR
AII and Heterogeneous Design with - ICAR

... In order to present some motivation for the methods proposed certain model-theoretic concepts are reviewed and some new techniques are presented. The Henkin style proof for Godel's completeness theorem is implemented by defining a model directly from the syntax of theories[21]. A model is defined by ...
then
then

... Coordination = the process by which an agent reasons about its local actions and the (anticipated) actions of others to try to ensure the community acts in a coherent manner ...
The AI Rebellion: Changing the Narrative
The AI Rebellion: Changing the Narrative

... Coman, Gillespie, and Muñoz-Avila (2015) proposed Rebel Agents in a limiting context of goal reasoning. We expand and generalize their definition. To our knowledge, a general formal framework for AI rebellion does not exist, although several authors have addressed (using varied terminology) what we ...
The AI Rebellion: Changing the Narrative
The AI Rebellion: Changing the Narrative

... Coman, Gillespie, and Muñoz-Avila (2015) proposed Rebel Agents in a limiting context of goal reasoning. We expand and generalize their definition. To our knowledge, a general formal framework for AI rebellion does not exist, although several authors have addressed (using varied terminology) what we ...
Spring Symposium Series - Association for the Advancement of
Spring Symposium Series - Association for the Advancement of

... understanding is pragmatically determined by the goals of the overall system. For this reason, the symposium welcomes participants who would not normally consider themselves to be working on natural language, but who are interested in how natural language could be a part of their research. This symp ...
Software Agents - UMBC Agent Web
Software Agents - UMBC Agent Web

... growing movement to study a much broader range of agent types, from the moronic to the moderately smart. The emphasis has subtly shifted from deliberation to doing; from reasoning to remote action. The very diversity of applications and approaches is a key sign that software agents are becoming main ...
< 1 2 3 4 5 6 7 8 9 10 ... 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