Heterogeneous temporal probabilistic agents

Abstract

To date, there has been no work on temporal probabilistic agent reasoning on top of heterogeneous legacy databases and software modules. We will define the concept of a heterogeneous temporal probabilistic (HTP) agent. Such agents can be built on top of existing databases, data structures, and software code bases without explicitly accessing the internal code of those systems and can take actions compatible with a policy or operating principles specified by an agent developer. We will develop a formal semantics for such agents through the notion of a feasible temporal probabilistic status interpretation (FTPSI for short). Intuitively, an FTPSI specifies what all an HTP agent is permitted/forbidden/obliged to do at various times t . As changes occur in the environment, the HTP agent must compute a new FTPSI. HTP agents continuously compute FTPSIs in order to determine what they should do and, hence, the problem of computing FTPSIs is very important. We give a sound and complete algorithm to compute FTPSIs for a very large class of HTP agents called strict HTP agents. In a given state, many FTPSIs may exist. These represent alternative courses of action that the HTP agent can take. We provide a notion of an optimal FTPSI that selects an FTPSI optimizing an objective function and give a sound and complete algorithm to compute an optimal FTPSI.