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A Medical Diagnosis System based on MAS Technology and Neural
A Medical Diagnosis System based on MAS Technology and Neural

... best-known expert system in this direction is MYCIN (cf. [Sh76], [BS84]). It is a program for advising physicians on treating bacterial infections of the blood and meningitis. Even though MYCIN does not exhibit common sense it does reasonably well, provided the user has common sense and understands ...
pdf file
pdf file

... in the non-human case. Organisational structure is used as a means to handle these complex dynamics. It provides a structuring of the processes in such a manner that an agent involved can function in a more appropriate manner. For example, at least partly the behavioural alternatives for the other a ...
Global Optimization for Multiple Agents - Infoscience
Global Optimization for Multiple Agents - Infoscience

... agents have preferences over these outcomes. A solution to a coordination problem is thus a feasible outcome that maximizes the local preferences of the different agents. An example of a coordination problem can be found in logistics. Being able to efficiently distribute goods using couriers has lar ...
Model Checking - Teaching-WIKI
Model Checking - Teaching-WIKI

... a formula (whether a formula α holds in all models) ⊨α • Utilizes the proof inference technique in some proof system • Problem is transformed to a sequent, a working representation for the theorem proving problem • The simplest sequent used in natural deduction: ⊢ α • A sequent holds when it satisfi ...
- University of Huddersfield Repository
- University of Huddersfield Repository

... sequence of actions (training data in the form of plan traces), where each action in a plan is stated as a name and a list of objects that the action refers to. For some domains which require static knowledge, there is a need to mention static preconditions for the domain to be learnt; as LOCM and L ...
Architectures for Robot Control
Architectures for Robot Control

... “ AI researchers ... partition the problems they work on into two components. The AI component, which they solve, and the nonAI component which they don’t solve. Typically AI ’succeeds’ by defining the parts of the problem that are unsolved as not AI. The principal mechanism for this partitioning is ...
session02_deron
session02_deron

... • Complex patterns of behavior emerge from their interaction. • Benefits: robustness, fast response time • Challenges: scalability, how intelligent? and how do you debug them? AI chapter 2 ...
Stojanov
Stojanov

... meaning? Are they all innate? How can we account for the productivity and systematicity in human representational system? Those are some of the issues that were and still are in the focus of cognitive science and the related fields. Despite the continuing discussions about the nature of representati ...
Towards Model-Based Diagnosis of Coordination Failures
Towards Model-Based Diagnosis of Coordination Failures

... diagnosis procedure for behavior-based agents, which utilized a model of behaviors that the agents should be in agreement on (i.e., concurrence coordination). However, their approach was specific only to agreements. ...
Belief Revision in Multi-Agent Systems
Belief Revision in Multi-Agent Systems

... complete coherence between all of the agents' conclusions all of the time. However attainment of this level of coherence depends not only on the system's architecture and design but also on the amount of inter-agent communication which is acceptable. Whenever a centralized architecture is appropriat ...
Directionally Selective Complex Cells and the Computation of
Directionally Selective Complex Cells and the Computation of

... was 0.4. Responses were sampled in 16 periodic increments in time, t, beginning with the time of stimulus Cortical 1-bar tests presentation, and also 16 samples in one-dimensional To study DS we began by reducing the stepwise (1D) space. The number of samples plotted was chosen movement sequence to ...
Non-rigid structure from motion using quadratic deformation models
Non-rigid structure from motion using quadratic deformation models

... can deal with challenging sequences where algorithms based on the former linear bases model sometimes fail to converge. Moreover, since the formulation is bilinear, the quadratic model fits nicely into the NRSfM framework. The main contribution of this paper is to introduce a physically grounded def ...
A GPU-accelerated cortical neural network model for visually guided
A GPU-accelerated cortical neural network model for visually guided

... & Mingolla, 2009), and none of them have been tested in realworld environments. The real world is the ultimate test bench for a model that is trying to link perception to action, because even carefully devised simulated experiments typically fail to transfer to real-world settings. Real environments ...
Lecture Notes in Computer Science - AIAI
Lecture Notes in Computer Science - AIAI

...  It is possible to enclose problems in local subteams, instead of spreading them along the entire organisation. We are considering hierarchical organisations arranged into three levels of decision-making: strategic, operational and tactical. However this is not a “must restriction” so that hierarc ...
2012-09-26 - Computer Science
2012-09-26 - Computer Science

... of problems they (intelligent machines) can handle will be coextensive with the range to which the human mind has been applied.) not kept • no general success in machine translation “The spirit is willing but the flesh is weak.” (into Russian and back) “The vodka is good but the meat is rotten.” • L ...
Biomechanics Models Motor Cortex Using Spinal Cord and Limb
Biomechanics Models Motor Cortex Using Spinal Cord and Limb

... signal nor does it represent motorneuron activity although it is closely related to them. In particular, the relation between muscular force and its control signal is not identical with the dynamics of an anatomical muscle (or with a combined action of several anatomical muscles, in case of a simpli ...
mul tiagent systems a modern approach to distributed artificial
mul tiagent systems a modern approach to distributed artificial

... "agent" without a corresponding consensuson what it means. Some researchers,such as Nwana (1996) sp1itsagent research into two main strands: the first beginning about 1977 with the works ofHewitt, whose roots are main1y in distributed artificial inte11igence(DAI), and the second around 1990 is a rec ...
AIME07.pdf
AIME07.pdf

... The clinical guideline used is the Dutch breast cancer guideline3 and was represented as a state transition system in Cadence SMV using the techniques and representation described in [2]. The models used here were developed as part of the Protocure-II project.4 Patient data were obtained from the Du ...
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-171-01-Agents_smrq16
cs-171-01-Agents_smrq16

... • Rationality is distinct from omniscience (all-knowing with infinite knowledge) • Agents can perform actions in order to modify future percepts so as to obtain useful information (information gathering, exploration) • An agent is autonomous if its behavior is determined by its own percepts & experi ...
Camera-ready Manuscript for the Proceedings of icame 2009
Camera-ready Manuscript for the Proceedings of icame 2009

... means that it has control over personal actions and inner state. Such system should also be capable of learning by experience. Possibility of interaction with the surroundings and autonomy of computer systems is not a new idea. There are already many systems of that kind, such as programmes for real ...
A New Fixpoint Semantics for General Logic Programs Compared
A New Fixpoint Semantics for General Logic Programs Compared

... 2.1. Theorem. For a general logic program P , the well-supported models of P are exactly the stable models of P . Proof. If M is a stable model of P , let ≺ be the strict well-founded partial ordering on M defined by A ≺ B iff for some integer i, A ∈ TH(P,M ) ↑ i and B ∈ TH(P,M ) ↑ i + 1\TH(P,M ) ↑ ...
cs-171-01-Agents
cs-171-01-Agents

... • Rationality is distinct from omniscience (all-knowing with infinite knowledge) • Agents can perform actions in order to modify future percepts so as to obtain useful information (information gathering, exploration) • An agent is autonomous if its behavior is determined by its own percepts & experi ...
On Line Isolated Characters Recognition Using Dynamic Bayesian
On Line Isolated Characters Recognition Using Dynamic Bayesian

... The International Arab Journal of Information Technology, Vol. 8, No. 4, October 2011 Table 1. Bayesian model: recognition rates of the letters A to H. ...
From Agent Theory to Agent Construction: A Case Study
From Agent Theory to Agent Construction: A Case Study

... In short, we propose a four-tiered hierarchy of entities comprising entities, objects, agents and autonomous agents. The basic idea underlying this hierarchy is that all components of the world are entities. Of these entities, some are objects, of which some, in turn, are agents and of these, some a ...
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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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