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Task Analysis Environment Modeling Simulation
Task Analysis, Environment Modeling, and Simulation (TAEMS or TÆMS) is a problem domain independent modeling language used to describe the task structures and the problem-solving activities of intelligent agents in a multi-agent environment.{{cite web , author=Bryan Horling , author2=Victor Lesser , author3=Regis Vincent , author4=Tom Wagner , author5=Anita Raja , author6=Shelley Zhang , author7=Keith Decker , author8=Alan Garvey , title=The Taems White Paper , year=1999 , url=https://mas.cs.umass.edu/research_old/taems/white/taemswhite.pdf , location=Multi-Agent Systems Lab , publisher=University of Massachusetts The intelligent agent operates in environments where: * responses by specific deadlines may be required * the information required for the optimal performance of a computational task may not be available * the results of the computations of multiple agents to interdependent subproblems may need to be aggregated together in order to solve a high-level goal * an agent may ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Modeling Language
A modeling language is any artificial language that can be used to express information or knowledge or systems in a structure that is defined by a consistent set of rules. The rules are used for interpretation of the meaning of components in the structure. Overview A modeling language can be graphical or textual. * ''Graphical'' modeling languages use a diagram technique with named symbols that represent concepts and lines that connect the symbols and represent relationships and various other graphical notation to represent constraints. * ''Textual'' modeling languages may use standardized keywords accompanied by parameters or natural language terms and phrases to make computer-interpretable expressions. An example of a graphical modeling language and a corresponding textual modeling language is EXPRESS. Not all modeling languages are executable, and for those that are, the use of them doesn't necessarily mean that programmers are no longer required. On the contrary, execut ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Problem-solving
Problem solving is the process of achieving a goal by overcoming obstacles, a frequent part of most activities. Problems in need of solutions range from simple personal tasks (e.g. how to turn on an appliance) to complex issues in business and technical fields. The former is an example of simple problem solving (SPS) addressing one issue, whereas the latter is complex problem solving (CPS) with multiple interrelated obstacles. Another classification is into well-defined problems with specific obstacles and goals, and ill-defined problems in which the current situation is troublesome but it is not clear what kind of resolution to aim for. Similarly, one may distinguish formal or fact-based problems requiring psychometric intelligence, versus socio-emotional problems which depend on the changeable emotions of individuals or groups, such as tactful behavior, fashion, or gift choices. Solutions require sufficient resources and knowledge to attain the goal. Professionals such as ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Automated Planning And Scheduling
Automation describes a wide range of technologies that reduce human intervention in processes, namely by predetermining decision criteria, subprocess relationships, and related actions, as well as embodying those predeterminations in machines. Automation has been achieved by various means including mechanical, hydraulic, pneumatic, electrical, electronic devices, and computers, usually in combination. Complicated systems, such as modern factories, airplanes, and ships typically use combinations of all of these techniques. The benefit of automation includes labor savings, reducing waste, savings in electricity costs, savings in material costs, and improvements to quality, accuracy, and precision. Automation includes the use of various equipment and control systems such as machinery, processes in factories, boilers, and heat-treating ovens, switching on telephone networks, steering, and stabilization of ships, aircraft, and other applications and vehicles with reduced ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Multi-agent Planning
In computer science multi-agent planning involves coordinating the resources and activities of multiple '' agents''. NASA says, "multiagent planning is concerned with planning by (and for) multiple agents. It can involve agents planning for a common goal, an agent coordinating the plans (plan merging) or planning of others, or agents refining their own plans while negotiating over tasks or resources. The topic also involves how agents can do this in real time while executing plans (distributed continual planning). Multiagent scheduling differs from multiagent planning the same way planning and scheduling differ: in scheduling often the tasks that need to be performed are already decided, and in practice, scheduling tends to focus on algorithms for specific problem domains". See also *Automated planning and scheduling * Distributed artificial intelligence * Cooperative distributed problem solving and Coordination Coordination may refer to: * Coordination (linguistics), a compoun ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Multi-agent Systems
A multi-agent system (MAS or "self-organized system") is a computerized system composed of multiple interacting intelligent agents.Hu, J.; Bhowmick, P.; Jang, I.; Arvin, F.; Lanzon, A.,A Decentralized Cluster Formation Containment Framework for Multirobot Systems IEEE Transactions on Robotics, 2021. Multi-agent systems can solve problems that are difficult or impossible for an individual agent or a monolithic system to solve.Hu, J.; Turgut, A.; Lennox, B.; Arvin, F.,Robust Formation Coordination of Robot Swarms with Nonlinear Dynamics and Unknown Disturbances: Design and Experiments IEEE Transactions on Circuits and Systems II: Express Briefs, 2021. Intelligence may include methodic, functional, procedural approaches, algorithmic search or reinforcement learning.Hu, J.; Bhowmick, P.; Lanzon, A.,Group Coordinated Control of Networked Mobile Robots with Applications to Object Transportation IEEE Transactions on Vehicular Technology, 2021. Despite considerable overlap, a multi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Software Agent
In computer science, a software agent or software AI is a computer program that acts for a user or other program in a relationship of agency, which derives from the Latin ''agere'' (to do): an agreement to act on one's behalf. Such "action on behalf of" implies the authority to decide which, if any, action is appropriate. Agents are colloquially known as '' bots'', from ''robot''. They may be embodied, as when execution is paired with a robot body, or as software such as a chatbot executing on a phone (e.g. Siri) or other computing device. Software agents may be autonomous or work together with other agents or people. Software agents interacting with people (e.g. chatbots, human-robot interaction environments) may possess human-like qualities such as natural language understanding and speech, personality or embody humanoid form (see Asimo). Related and derived concepts include ''intelligent agents'' (in particular exhibiting some aspects of artificial intelligence, such as r ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Distributed Artificial Intelligence
Distributed Artificial Intelligence (DAI) also called Decentralized Artificial Intelligence is a subfield of artificial intelligence research dedicated to the development of distributed solutions for problems. DAI is closely related to and a predecessor of the field of multi-agent systems. Definition Distributed Artificial Intelligence (DAI) is an approach to solving complex learning, planning, and decision making problems. It is embarrassingly parallel, thus able to exploit large scale computation and spatial distribution of computing resources. These properties allow it to solve problems that require the processing of very large data sets. DAI systems consist of autonomous learning processing nodes ( agents), that are distributed, often at a very large scale. DAI nodes can act independently and partial solutions are integrated by communication between nodes, often asynchronously. By virtue of their scale, DAI systems are robust and elastic, and by necessity, loosely coupled. Fur ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Cooperative Distributed Problem Solving
In computing cooperative distributed problem solving is a network of semi-autonomous processing nodes working together to solve a problem, typically in a multi-agent system. That is concerned with the investigation of problem subdivision, sub-problem distribution, results synthesis, optimisation of problem solver coherence and co-ordination. It is closely related to distributed constraint programming and distributed constraint optimization; see the links below. Aspects of CDPS * Neither global control or global data storage – no individual CDPS problem solver (agent) has sufficient information to solve the entire problem. * Control and data are distributed * Communication is slower than computation, therefore: ** Loose coupling between problem solvers ** Efficient protocols (not too much communication overhead) ** problems should be modular, coarse grained * Any unique node is a potential bottleneck ** Organised behaviour is hard to guarantee since no one node has the complete p ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Stanford Research Institute Problem Solver
The Stanford Research Institute Problem Solver, known by its acronym STRIPS, is an automated planner developed by Richard Fikes and Nils Nilsson in 1971 at SRI International. The same name was later used to refer to the formal language of the inputs to this planner. This language is the base for most of the languages for expressing automated planning problem instances in use today; such languages are commonly known as action languages. This article only describes the language, not the planner. Definition A STRIPS instance is composed of: * An initial state; * The specification of the goal states – situations which the planner is trying to reach; * A set of actions. For each action, the following are included: ** preconditions (what must be established before the action is performed); ** postconditions (what is established after the action is performed). Mathematically, a STRIPS instance is a quadruple \langle P,O,I,G \rangle, in which each component has the following meanin ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Hierarchical Task Network
In artificial intelligence, hierarchical task network (HTN) planning is an approach to automated planning in which the dependency among actions can be given in the form of hierarchically structured networks. Planning problems are specified in the hierarchical task network approach by providing a set of tasks, which can be: # primitive (initial state) tasks, which roughly correspond to the actions of STRIPS; # compound tasks (intermediate state), which can be seen as composed of a set of simpler tasks; # goal tasks (goal state), which roughly corresponds to the goals of STRIPS, but are more general. A solution to an HTN problem is then an executable sequence of primitive tasks that can be obtained from the initial task network by decomposing compound tasks into their set of simpler tasks, and by inserting ordering constraints. A primitive task is an action that can be executed directly given the state in which it is executed supports its precondition. A compound task is a comp ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
