The complexity of the modern information carrying landscape requires a sophisticated view in which information is acquired rather than simply retrieved; where the process must be dynamic, incremental, and constrained by resource limitations. Information Gathering (IG) is an activity involving pro-active acquisition of information, from possibly heterogeneous sources, in response to a complex query that may require the system to possess capabilities such as reasoning, representation and inferencing. In this paper, we present a model of information gathering designed specifically for such complex environments, a model of Cooperative Information Gathering (CIG). addition to the complexity of query specification, control of the acquisition process may itself be complex and dynamic in IG systems. Traditional Information Retrieval (IR) is a limited sub-case of such information gathering systems in which queries generally map onto static, pre-specified retrieval plans. In this paper, we propose a cooperative agent-based solution for information gathering. Top level queries drive the creation of partially elaborated information gathering plans, resulting in the employment of multiple semi-autonomous, cooperative agents for the purpose of achieving goals and subgoeds within those plans. Cooperation between agents implies management of interdependencies between their activities so as to integrate and evolve consistent clusters of high quality information from distributed heterogeneous sources. This paper draws upon a long history of thought in Distributed Problem Solving (DPS) to present model of this type of cooperative information acquisition.