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Topic: Reasoning agent

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	Agent Oriented Software (AOS) - JACK Intelligent Agents, software agent system.
		The Agent Oriented Software Group (AOS) is the world's leading developer and supplier of software products for building and deploying agent-oriented applications.
		Commercially deployed worldwide, JACK-based systems are built from distributed reasoning entities that cooperate to achieve their goals.
		Norwegian-based Statoil, one of the world’s largest suppliers of crude oil and natural gas, is developing software to support oil trading and operations management, using the JACK intelligent agent development toolkit from Agent Oriented Software (AOS), with additional application development support from Cambridge Consultants.
	www.agent-software.com (265 words)

	Wendelin Reich: Reasoning About Other Agents
		Both agents carry out social meta-reasoning in response to observable behavior and both agents assume that the respective other carries it out (e.g., agent 1 when she interprets agent 2's small adjustment as "goodwill"; agent 2 when he reconstructs agent 1's reconstruction of his own subjective valuation of the good).
		Likewise, reasoning such as, "A drastically adjusted price reveals that the agents believes her good is worth little" cannot be represented in classical game theory because it involves incomplete information, and it cannot be represented as a game of incomplete information (e.g., a signaling game, Owen 1995: p.
		Thus, agents can be characterized as processes that apply rules to their own properties according to the laws of a specific logical calculus, thereby transforming a set of initial states (e.g., perceptions) into a set of final states (e.g., actions).
	jasss.soc.surrey.ac.uk /7/4/4.html (6827 words)

	Autonomous learning and reasoning agent
		In a preferred embodiment, the autonomous agent may be implemented in a case-based reasoning system, which may be coupled to a sensor for gathering information from, and to an effector for manipulating, its environment (which may comprise a software environment, a physical environment, or some combination thereof).
		A software agent 101 may be embedded in an environment 102 so that the agent 101 may receive a stimulus 103 from the environment 102 by receiving a stimulus message 104, and may perform an action 105 which affects the environment 102 by sending an action message 106.
		In a preferred embodiment, the software agent 101 may be implemented with an automated processor 124, which may execute a software inference engine 125 for reasoning using a set of cases 126 in a case base 127 and a set of rules 128 in a rule base 129.
	www.freepatentsonline.com /5852814.html (4809 words)

	Moral Reasoning (Stanford Encyclopedia of Philosophy)
		This article takes up moral reasoning as a species of practical reasoning — that is, as a type of reasoning directed towards deciding what to do and, when successful, issuing in an intention (see entry on practical reason).
		When this reasoning by analogy starts to become systematic — a social achievement that requires some historical stability and reflectiveness about what are taken to be moral norms — it begins to exploit comparison to cases that are “paradigmatic,” in the sense of being taken as settled.
		From the epistemically limited standpoint of moral reasoning, however, the interesting question, from the point of view of the theory of moral reasoning, is whether agents are authorized by their roles to give special prominence to certain considerations in their moral deliberation and to ignore others.
	plato.stanford.edu /entries/reasoning-moral (12340 words)

	Agent or Program (Site not responding. Last check: 2007-10-29)
		A spell checker adjunct to a wordprocessor is typically not an agent for the reasons given in the preceding paragraph.
		Agents may also be classified by the range and sensitivity of their senses, or by the range and effectiveness of their actions, or by how much internal state they possess.
		For example, when a collection of scheduling agents gather to schedule a meeting between their users, they pursue a common goal and intelligent group behavior emerges (see Kautz, Selman, and Coen 1994 for a similar situation.) Yet, as a group, our definition of agent is not met in that persistence is missing.
	www.msci.memphis.edu /~franklin/AgentProg.html (4230 words)

	Experiments with an Agent-oriented Reasoning System
		Whereas many hard-wired integrations of reasoning systems have been shown to be fruitful, rather few architectures have been discussed so far that try to extend the application range of reasoning systems by a flexible integration of a variety of specialist systems.
		The former is achieved by providing a declarative agent specification language and mechanisms supporting the definition, addition, or deletion of reasoning agents (as well as some other proof search critical components and heuristics) even at run-time.
		The agent paradigm was chosen to enable a more flexible integration approach, and to overcome some of the limitations of hardwired integrations (for instance, the brittleness of traditional proof planning where external systems are typically called within the body of proof methods and typically do not cooperate very flexibly).
	www.cs.bham.ac.uk /~mmk/papers/01-KI.html (6057 words)

	O-ANTS -- An Agent Based Approach to Reasoning (Site not responding. Last check: 2007-10-29)
		Resource management is employed to distribute available resources amongst the available reasoning agents in order to determine their maximum reasoning time and to prevent them from a quick consumption of all available resources.
		Generally our approach supports parallelization of reasoning tasks on term level, inference level, and proof search level and external systems can not only be employed to support object level proof search but also to support meta-level reasoning, for instance, by checking complicate application conditions of inference rules.
		The task of the O-ANTS agents (the knowledge sources of the flboards) is to test the applicability of rules, tactics, methods, and external reasoners in a given proof state and to suggest appropriate parameter instantiations for them.
	www.ags.uni-sb.de /~omega/research/agentsTP (988 words)

	Autonomous learning and reasoning agent
		An autonomous software agent as in claim 3, wherein said means for selecting a case for case-based reasoning is responsive to a plurality of measures.
		An autonomous software agent as in claim 1, wherein said means for selecting a set of matching cases from said case base comprises means for applying a random effect or a pseudorandom effect to a measure of match quality, case accuracy, or case utility.
		An autonomous software agent as in claim 1, wherein said means for selecting a set of matching cases from said case base is more likely to select a case with a greater measure of match quality, case accuracy, or case utility.
	www.freepatentsonline.com /5586218.html (6814 words)

	Intelligent Software Agent Bibliography - Steve Gant (Site not responding. Last check: 2007-10-29)
		Reasoning about intentions is an important area of research for the design of resource bounded rational agents who need to coordinate their actions with the actions of other agents in a multi-agent system.
		Commitments ensure that agents reason to achieve their intentions, however a commitment can also be dropped if it is considered irrational by the agent to continue acting for its associated intention.
		Guides are a simple form of agents who assume the roles of storytellers, and their success is to be measured not by the stringent requirements of full-blown intelligent agents, but against the softer criteria of plausibility and suspension of disbelief.
	ils.unc.edu /gants/agentbib.html (13559 words)

	Agents at RMIT
		Hence one approach to the development of agent systems is to start with the paradigm of logic programming, which provides both reasoning and programming facilities, and to extend and modify it to incorporate the various features of agent systems, such as reactivity, autonomy, social abilities and so forth.
		Agent Cities is a project run by FIPA, partly to use and test the agents standards which they are developing.
		Agent oriented systems are a growing area and the field of agent oriented software engineering is in its infancy.
	www.cs.rmit.edu.au /agents (4571 words)

	Why explicit knowledge is not enough
		Reliability implies that the agent is able to select deterministically a suitable procedure for the input and compute the answer within finite time.
		The first question is answered by specifying the logic used by agents in their reasoning, and the second one by a complexity analysis.
		What an agent knows or can derive from his knowledge is determined by the logic he uses in his reasoning.
	www.informatik.uni-leipzig.de /~duc/Thesis/node35.html (575 words)

	Invited Lecture, Oct. 2000, Ushuaia, Argentine
		Although there have been developed in the last years a huge variety of techniques and methods related to agents, a well-defined theoretical foundation unifying the different facets under one umbrella is still missing.
		Agents must be able to reason with beliefs, time, uncertainty and security.
		We extend agent programs by beliefs: agents are allowed to have beliefs about others and to use them in their programs: meta agent programs.
	www.in.tu-clausthal.de /~dix/LECTURING/usuahia.html (868 words)

	Jaime Simão Sichman: DEPINT: Dependence-Based Coalition Formation in an Open Multi-Agent Scenario
		This way, an agent may dynamically choose a goal to pursuit and a plan to achieve it, being sure that every skill needed to accomplish the selected plan is available in the society.
		Because agents' interactions are guided by their information about the others, it is exactly during these interactions that they may detect that this information is either incorrect or incomplete, and eventually revise it.
		The last is justified by the fact that a possible reason for an agent to refuse to take part in a coalition is because the sender has a false belief about his capabilities: the sender may believe that the agent can perform an action, when in fact this is not true.
	jasss.soc.surrey.ac.uk /1/2/3.html (7618 words)

	Professor Ron Sun
		Yet another focus is the development of modular reinforcement learning models, in which multiple modules (or agents) compete and cooperate with each other to accomplish tasks, without a priori division of the tasks (i.e., without using any a priori domain-specific knowledge).
		This type of reasoning was characterized by a mixture of rule-based and similarity-based processes, exhibiting both rigor and flexibility (as demonstrated in my AIJ paper).
		To capture such reasoning, I developed a hybrid connectionist architecture (named CONSYDERR) with both localist and distributed components, that unified rule-based and similarity-based processes and accounted for a variety of CSR patterns.
	www.cogsci.rpi.edu /~rsun (3348 words)

	News Story \| Virginia Tech News \| Virginia Tech
		The research project integrates NuTech’s Geospatial Agent-Based Reasoning (GeoABR) software with Virginia Tech’s ultra high resolution analytical workstation displays.
		The demonstration of these scientific programs will highlight the capabilities of the two leading edge solutions, as they are transitioned to a developmental stage for application in future geospatial analytical systems used by U.S. government agencies.
		The graphical user interface developed in collaboration with Virginia Tech geographers and HCI researchers allows non-programmers to create and modify rule sets for applications such as data triage and identification of areas of potential interest, as well as precisely tailored searches and early warning systems.
	www.vtnews.vt.edu /story.php?relyear=2006&itemno=596 (404 words)

	Intelligent Agent Reasoning
		The BDI model comes from research done in the field of artificial intelligence over the past twenty years and has proven to be the most robust and flexible model for Intelligent Agent Systems.
		set of plans that are combinations of actions which achieve certain outcomes or respond to events and are used by the agent to further its intentions.
		This enables the agent to be more or less sensitive to changes in the environment, that is, be more or less "committed" to its current plan.
	www.agent-software.com /shared/home/reasoning.html (309 words)

	ASDL:Reasoning-Agent - Wiki
		Wenn der Agent die "getsuggestion"-Nachricht bekommt, werden die zwischengespeicherten Suggestions, d.h.
		Wenn der Agent die acceptedsuggestion-Nachricht erhält, kann die mitgelieferte Suggestion-ID in die Datenbank abgespeichert werden.
		Der dazugehörige Case wird aus den Kontextdaten der Nachricht konstruiert.
	www.is.informatik.uni-duisburg.de /wiki/index.php/ASDL:Reasoning-Agent (751 words)

	AgentLink.org \| European Co-ordination Action for Agent-Based Computing
		The theory of PRS-like systems has also been widely studied: within the intelligent agents research community, the belief-desire-intention (BDI) model of practical reasoning that underpins PRS is arguably the dominant force in the theoretical foundations of rational agency.
		Despite the interest in PRS and BDI agents, no complete attempt has yet been made to precisely specify the behaviour of real PRS systems.
		This has led to the development of a range of systems that claim to conform to the PRS model, but which differ from it in many important respects.
	eprints.agentlink.org /2135 (326 words)

	ADMW 2003: Knowledge Representation and the Reasoning Agent :: Background
		The Second Augustus De Morgan Workshop dealt with the history of logic, taking the view that there is a historical continuity in trying to logically model the human.
		This was in response to the realisation in the AI community, that much of the logic research in ancient and medieval logic was the result of attempts to analyse human (theological) reasoning and was therefore directly potentially relevant to current AI and argumentation problems.
		Probability is a major component in common sense reasoning that so far has been developed side-by-side with the new logic.
	www.dcs.kcl.ac.uk /research/groups/gllc/ADMW03/background.html (658 words)

	Multi-Agent Reasoning with Belief Contexts III: Towards the Mechanization - Cimatti, Serafini (ResearchIndex) (Site not responding. Last check: 2007-10-29)
		Agents That Reason and Negotiate By Arguing - Parsons, Sierra, Jennings (1998)
		Multi-agent reasoning with belief contexts III: Towards the mechanization.
		5 A Foundation of Metalogical Reasoning: OM pairs (context) - Criscuolo, Giunchiglia et al.
	citeseer.ist.psu.edu /194081.html (633 words)

	ECS EPrints Service - The dMARS Architechure: A Specification of the Distributed Multi-Agent Reasoning System
		The theory of PRS-like systems has also been widely studied: within the intelligent agents research community, the belief-desire-intention (BDI) model of practical reasoning that underpins PRS is arguably the dominant force in the theoretical foundations of rational agency.
		Despite the interest in PRS and BDI agents, no complete attempt has yet been made to precisely specify the behaviour of real PRS systems.
		This has led to the development of a range of systems that claim to conform to the PRS model, but which differ from it in many important respects.
	eprints.ecs.soton.ac.uk /10224 (311 words)

	ActiveRain Real Estate Network
		Most agents have Web sites by now, but you know my views on their effectiveness: most of them don't earn money for the agent.
		Those agents who do make money from their sites keep up on what helps make their site accessible and effective.
		These real estate profiles, blogs and blog entries are provided here as a courtesy to our visitors to help them make an informed decision when buying or selling a house.
	www.activerain.com (750 words)

	[No title]
		Slater's argument trades on the notion of contradictoriness in the attempt to show that the negation of paraconsistent logics is merely a subcontrary forming operator and not one which forms contradictories.
		Our further goal is to put these logics in the service of practical reasoning systems, since the basic concept of our treatment is that of an agent a reasoning to conclusions using as assumptions the theory of agent b, where a and b may or may not be the same.
		Experimental studies conducted in a very difficult area of theorem proving, namely equational reasoning, demonstrate the capacity of the techniques and underline their potential to be a very useful tool for eliminating human interaction requiring expert knowledge.
	arp.anu.edu.au /ftp/techreports/abstracts.txt (8524 words)

	Frameworks for Reasoning about Agent Based Systems TITLE2: (Site not responding. Last check: 2007-10-29)
		This paper suggests formal frameworks that can be used as the basis for defining, reasoning about, and verifying properties of agent systems.
		We demonstrate that the semantics of Little-JIL are sufficiently well defined to support the application of static dataflow analysis, enabling the verification of critical properties of the agent systems.
		This approach is inherently a top-down approach that complements bottom-up approaches to reasoning about system behavior.
	www.cs.umass.edu /Dienst/UI/2.0/Describe/ncstrl.umassa_cs%2fUM-CS-2000-034 (138 words)

	CiteULike: Agent Reasoning Mechanism for Long-Term Coalitions Based on Decision Making and Trust (Site not responding. Last check: 2007-10-29)
		CiteULike: Agent Reasoning Mechanism for Long-Term Coalitions Based on Decision Making and Trust
		Agent Reasoning Mechanism for Long-Term Coalitions Based on Decision Making and Trust
		Note: You or your institution must have access rights to this article.
	www.citeulike.org /user/mathijs/article/322146 (68 words)

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