Abstract
from the last two decades, Software agents are playing an important role in the field of Artificial intelligence and the Distributed Problem Solving. The properties of software agents like autonomy, reactivity, pro-activity and their social ability make them more center of focus for the real world problems. The accomplishment of any complex task is required to be done by the agents autonomously without any user intervention in order to achieve high reliability and adaptability. This paper mainly concentrates on the task allocation problem in multi-agent systems. Task Allocation is an important and challenging problem. This can be defined as the problem of allocating tasks among agents within a multi-agent system. Main objective of the task allocation problem is to maximize the number of successfully completed task and overall system utility without any conflict. To accomplish any complex task, agents negotiate, cooperate and coordinate with each other. Many researchers are working in the field of task allocation in multiagent systems. In this paper, various approaches of task allocation in multi-agent systems are discussed. The comparison of these approaches is also providing that lead to a discussion and motivation of the task allocation problem for multi-agent systems. This paper presents a hybrid approach for task allocation in dynamic multi-agent systems. The conclusion drawn from this survey is that, for dynamic multi-agent systems, the distributed task allocation is a better approach.