• Journal of the Korea Computer Industry Society
• /
• v.5 no.3
• /
• pp.363-370
• /
• 2004

The FIPA community is developing a range of agent-related standards, of which the centerpiece is an Agent Communication Language (ACL). This language includes a number of communicative acts explicitly intended to support negotiation. In this paper, we consider a multi-agent environment that exchanges the resources for achieving agents' goals, represent agents as computational logic-based formalizations, and describe a simple ACL for negotiation using logic-based agents. In particular, we introduce and compare some communication acts that enable counter-agents to know the reason of request(proposal) or the reason of rejection(refusal).

• Journal of the Korea Computer Industry Society
• /
• v.5 no.9
• /
• pp.1089-1094
• /
• 2004

Agents in Mlulti-Agent Systems (MAS) should make use of a common Agent Communication Language (ACL) in order to negotiate with others, and conform to negotiation protocols that are designed to reach agreements. Therefore, agents must have suitable architectures that could cover above requirements. In this paper, we define an instructive ACL and compare it with other ACLs such as Foundation for Intelligent Physical Agents(FIPA) ACL and Knowledge Query Manipulation Language (KQML). In particular, we represent agents as logic programs with beliefs, desires, intentions and negotiation library. Finally, we show how the planner, which is in the negotiation library, provides plans of actions and updates agent's beliefs.

• Transactions on Control, Automation and Systems Engineering
• /
• v.1 no.2
• /
• pp.147-152
• /
• 1999

It is an interesting area in the field of artifical intelligence to find an analytic model of cooperative structure for multiagent system accomplishing a given task. Usually it is difficult to design controllers for multi-agent systems without a comprehensive knowledge about the system. One of the way to overcome this limitation is to implement an evolutionary approach to design the controllers. This paper introduces the use of a genetic algorithm to discover a fuzzy logic controller with rules that govern emergent agents solving a pursuit problem in a continuous world. Simulation results indicate that, given the complexity of the problem, an evolutionary approach to find the fuzzy logic controller seems to be promising.

• 제어로봇시스템학회:학술대회논문집
• /
• 1998.10a
• /
• pp.507-512
• /
• 1998

It is an interesting area in the field of artificial intelligence to and an analytic model of cooperative structure for multi-agent system accomplishing a given task. Usually it is difficult to design controllers for multi-agent systems without a comprehensive knowledge about the system. One of the way to overcome this limitation is to implement an evolutionary approach to design the controllers. This paper introduces the use of a genetic algorithm to discover a fuzzy logic controller with rules that govern emergent co-operative behavior: A modified genetic algorithm was applied to automating the discovery of a fuzzy logic controller jot multi-agents playing a pursuit game. Simulation results indicate that, given the complexity of the problem, an evolutionary approach to and the fuzzy logic controller seems to be promising.

• Journal of Internet Computing and Services
• /
• v.8 no.1
• /
• pp.115-123
• /
• 2007

Agents in Multi-Agent System; (MAS) should make use of a common Agent Communication Language (ACL) in order to negotiate with others, and conform to negotiation protocols thatare designed to reach agreements. Therefore, agents must have suitable architectures that could cover above requirements. In this paper, we define an instructive ACL and compare it with other ACLs such as Foundation for Intelligent Physical Agents (FIPA) ACL and Knowledge Query Manipulation Language(KQML), In particular, we represent agents as logic programs with knowledge base and negotiation library. Finally, we show how the planner, which is in the negotiation library, provides the plan of actions and updates agent's knowledge base.

• Journal of Information Processing Systems
• /
• v.11 no.4
• /
• pp.630-642
• /
• 2015

In Jøsang's subjective logic, the fusion operator is not able to fuse three or more opinions at a time and it cannot consider the effect of time factors on fusion. Also, the base rate (a) and non-informative prior weight (C) could not change dynamically. In this paper, we propose an Improved Subjective Logic Model with Evidence Driven (ISLM-ED) that expands and enriches the subjective logic theory. It includes the multi-agent unified fusion operator and the dynamic function for the base rate (a) and the non-informative prior weight (C) through the changes in evidence. The multi-agent unified fusion operator not only meets the commutative and associative law but is also consistent with the researchers's cognitive rules. A strict mathematical proof was given by this paper. Finally, through the simulation experiments, the results show that the ISLM-ED is more reasonable and effective and that it can be better adapted to the changing environment.

• Journal of the Korea Society for Simulation
• /
• v.17 no.3
• /
• pp.9-18
• /
• 2008

Unlike conventional researches, we are able to i) compare the fuzzy logic based BBA with non-fuzzy BBA for verifying the effective performance of the proposed fuzzy logic application ii) dynamically respond to the intrusion using BBA whereas the previous IDS was responding statically and iii) expect that this would be a cornerstone for more practical application researches (analyzing vulnerability and examining countermeasures, etc.) of security simulation. Several simulation tests performed on the targer network will illustrate our techniques. And this paper applies fuzzy logic to reduce the false negative that is one of the main problems of IDS. Intrusion detection is complicated decision-making process, which generally involves enormous factors about the monitored system. Fuzzy evaluation component model, which is a decision agent in the distributed IDS, can consider various factors based on fuzzy logic when an intrusion behavior is detected. The performance obtained from the coordination of intrusion detection agent with fuzzy logic is compared against the corresponding non fuzzy type intrusion detection agent. The results of these comparisons allow us to evaluate a relevant improvement on the fuzzy logic based BBA.

• Korean Journal of Logic
• /
• v.13 no.1
• /
• pp.101-128
• /
• 2010

In this paper I explore the theory of agent causation proposed by T. O'Connor. According to the theory, we can't explain an agent's control over his intention and action without appealing to 'agent causes events'(shortly, ACEs). But I argue that ACEs can't be a help to an agent's control over his intention and action. For this I show that reason-responsiveness is a necessary condition for an agent's control. In order for ACEs to help in explaining an agent's control, ACEs must be able to satisfy 'reason-responsiveness condition'. But, ACEs fail to satisfy the condition. For this reason, I conclude that ACEs can't be a help to an agent's control over his intention and action.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.10 no.6
• /
• pp.584-590
• /
• 2000

Urban traffic situations are extremely complex and highly interactive. The multi-agent systems approach can provide a new desirable solution. Currently, a traffic simulator is needed to understand and explore the difficulties in an agent-oriented traffic control. This paper presents an agent-oriented fuzzy logic controller for multiple crossroads simulation. A fuzzy logic control simulation with variables of arrival, queue, and traffic volume could alleviate traffic congestion. We developed an agent-oriented simulator suitable for traffic junctions with η$\times$η intersections in Visual C++. The proposed method adaptively controls the cycle of traffic signals even though the traffic volume varies. The effectiveness of this method was shown through simulation of multiple intersections.

• 제어로봇시스템학회:학술대회논문집
• /
• 2002.10a
• /
• pp.93.5-93
• /
• 2002

Distributed Artificial Intelligence (DAI) aims to study and develop techniques that allow interaction among intelligent entities. In the last two decades, some types of DAI architecture have been proposed for various fields. However, it can be noticed that the inconsistency phenomenon has not been dealt with properly. This is probably due to the fact that this phenomenon cannot be handled (at least directly) with classical logic. Hence, to deal with such inconsistencies directly, one should employ a logic other than the classical one. The DAI Architecture described in this work is based on a nonclassical logic called Annotated Paraconsistent Logic.