Towards refinement of abductive or inductive hypotheses through propagation

Abstract

In this paper we address the problem of distributed sources of information, or agents, that observe the environment locally and have to communicate in order to refine their hypothesis regarding the actual state of this environment. One way to address the problem would be to centralize all the collected observations and knowledge, and to centrally compute the resulting theory. In many situations however, it would not be possible to adopt this centralized approach (e.g. for practical reasons, or privacy concerns). In this paper, we assume that agents individually face abductive or inductive tasks in a globally coherent environment, and we show that general mechanisms can be designed that abstractly regard both cases as special instances of a problem of hypothesis refinement through propagation. Assuming that agents are equipped with some individual revision machinery, our concern will be to investigate how (under what conditions) convergence to a consistent state can be guaranteed at more global levels: (i) between two agents; (ii) in a clique of agents; and (iii) in general in a connected society of agents.