Mohd Zaliman Mohd Yusoff

Using Genetic Algorithm for Traffic Light Control System with a Pedestrian Crossing

In this paper, we explore the use of genetic algorithm and implementing the technology to improve the performance of traffic light and pedestrian crossing control in a four-way, two-lane traffic junction. The algorithm resolves the limitations of traditional fixed-time control for passing vehicles and pedestrians. It employs a dynamic system to control the traffic light and pedestrian crossing that monitors two sets of parameters: the vehicle and pedestrian queues behind a red light and the number of vehicles and pedestrians that passes through a green light. The algorithm dynamically optimizes the red and green times to control the flow of both the vehicles and the pedestrians. Performance comparisons between the genetic algorithm controller and a fixed-time controller reveal that the genetic algorithm controller performs significantly better.

A Review of Norms and Normative Multiagent Systems

Norms and normative multiagent systems have become the subjects of interest for many researchers. Such interest is caused by the need for agents to exploit the norms in enhancing their performance in a community. The term norm is used to characterize the behaviours of community members. The concept of normative multiagent systems is used to facilitate collaboration and coordination among social groups of agents. Many researches have been conducted on norms that investigate the fundamental concepts, definitions, classification, and types of norms and normative multiagent systems including normative architectures and normative processes. However, very few researches have been found to comprehensively study and analyze the literature in advancing the current state of norms and normative multiagent systems. Consequently, this paper attempts to present the current state of research on norms and normative multiagent systems and propose a norms life cycle model based on the review of the literature. Subsequently, this paper highlights the significant areas for future work.

Norms Detection and Assimilation in Multi-agent Systems: A Conceptual Approach

In this paper, we propose a technique for a software agent to detect the norms of a community of agents and assimilate its behavior to comply with the local normative protocol, failing which, the agent is refused services and resources. In this technique, the software agent is equipped with an algorithm, which detects and analyzes the normative interactions between local agents. When the detection is successful, it launches another algorithm to request for its assimilation to the local normative protocol, indicating its acceptance by the group of local agents.

A Collaborative Framework for Multiagent Systems

In this paper, the authors demonstrate the use of software agents to extend the role of humans in a collaborative work process. The extended roles to agents provide a convenient means for humans to delegate mundane tasks to software agents. The framework employs the FIPA ACL communication protocol which implements communication between agents. An interface for each agent implements the communication between humans and agents. Such interface and the subsequent communication performed by agents and between agents contribute to the achievement of shared goals.

A Norm Assimilation Approach for Multi-agent Systems in Heterogeneous Communities

In a heterogeneous community, which constitutes a number of social groups that adopt different social norms, norm assimilation is considered as the main problem for a new member to join a desired social group. Studies in norm assimilation seem to be lacking in concept and theory within this research domain. Consequently, this paper proposes a norm assimilation approach, in which a new agent attempts to join a social group via assimilating with the social group’s norms. Several cases are considered for an agent’s decision which are, can assimilate, could assimilate, and cannot assimilate. We develop the norm assimilation approach based on the agent’s internal belief about its ability and its external belief about the assimilation cost of a number of social groups. From its beliefs about its ability and assimilation cost, it is able to decide whether to proceed or decline the assimilation with a specific social group or join another group.

Automated Multi-agent Negotiation Framework for the Construction Domain

In this paper, we propose an automated multi-agent negotiation framework for decision making in the construction domain. It enables software agents to conduct negotiations and autonomously make decisions. The proposed framework consists of two types of components, internal and external. Internal components are integrated into the agent architecture while the external components are blended within the environment to facilitate the negotiation process. The internal components are negotiation algorithm, negotiation style, negotiation protocol, and solution generators. The external components are the negotiation base and the conflict resolution algorithm. We also discuss the decision making process flow in such system. There are three main processes in decision making for specific projects, which are propose solutions, negotiate solutions and handling conflict outcomes (conflict resolution). We finally present the proposed architecture that enables software agents to conduct automated negotiation in the construction domain.

Potential norms detection in social agent societies

In this paper, we propose a norms mining algorithm that detects a domain’s potential norms, which we called the Potential Norms Mining Algorithm (PNMA). According to the literature, an agent changes or revises its norms based on variables of local environment and amount of thinking about its behaviour. Based on these variables, the PNMA is used to revise the norms and identify the new normative protocol to comply with the domain’s norms. The objective of this research is to enable an agent to revise its norms without a third party enforcement unlike most of the work on norms detection and identification, which entail sanctions by an authority. We demonstrate the execution of the algorithm by testing it on a typical scenario and analyse the results on several issues.

Modeling agent-based collaborative process

In this paper, we develop a model for a collaborative process using software agents to resolve issues and problems with the process. The structure, workflow, and entities of the process are analyzed to develop a model in which software agents take over the communicating tasks and motivating their human counterparts by reminding, alerting, and evaluating them to comply with scheduled deadlines. The model is used as a blueprint to develop a multi-agent system for the collaborative process.

Mitigating human-human collaboration problems using software agents

In this paper, we demonstrate the use of autonomous agents to assist humans in complying with the schedule of a collaborative work process. Software agents take over the tasks of communicating between agents and reminding and alerting humans in complying with scheduled tasks. While the FIPA agent communication language implements communication exchanges between agents, an interface for each agent implements the communication between humans and agents. Such interface provides a convenient means for humans to delegate mundane tasks to software agents.

A study of meditation effectiveness for virtual reality based stress therapy using eeg measurement and questionnaire approaches

Various approaches are available to evaluate the effectiveness of stress therapy. In this research, we compared virtual reality based stress therapy and imaginary technique which includes cultural elements such as typical Malaysian environment in 3D, Mozart, soothing breathing exercise and audio. It examines meditation effectiveness between virtual reality based stress therapy and imaginary technique using Electroencephalograph. The effectiveness of the virtual reality therapy and imaginary technique are measured by NeuroSky eSense Meditation level. Findings for both approaches indicated that there are positive changes in participants’ meditation state. Moreover, the virtual reality participants were observed to be in a better meditation state (significantly different) compared to the imaginary participants at the end of the study.