On Ability to Autonomously Execute Agent Programs with Sensing — Extended Abstract

There has been much work already on formal models of deliberation/planning under incomplete information, where an agent can perform sensing actions to acquire additional information. But most of it has been set in epistemic logicbased frameworks and is hard to relate to work on agent programming languages (e.g. 3APL, AgentSpeak(L)). Here, we develop new non-epistemic formalizations of deliberation that are much easier to relate to standard agent programming language semantics based on transition systems. When doing deliberation/planning under incomplete information, one typically searches over a set of states, each of which is associated with a knowledge base (KB) or theory that represents what is known in the state. To evaluate tests in the program and to determine what transitions/actions are possible, one looks at what is entailed by the current KB. To allow for future sensing results, one looks at which of these are consistent with the current KB. We call this type of approach to deliberation “entailment and consistencybased” (EC-based). In this paper, we argue that EC-based approaches do not always work, and propose an alternative. Our accounts are formalized within the situation calculus and use a simple programming language based on ConGolog to specify agent programs, but we claim that the results generalize to most proposed agent programming languages/frameworks. Our accounts rely on a semantics for online executions of programs with sensing. A configuration is a pair (δ,σ) involving a program δ and a history σ specifying the actions performed so far and the sensing results obtained. In the full paper, we define a transition relation for this, i.e. when a configuration (δ,σ) may evolve to configuration (δ ′,σ′) w.r.t. a model M (relative to an underlying theory of action D). The definition requires that the theory D, augmented with the sensing results in σ, entail that the transition is possible. The model M is used to represent a possible environment and generate sensing results. We also define when a configuration is final, i.e. may legally terminate. Perhaps the first approach to come to mind for defining when an agent knows how/is able to execute a deterministic program δ in a history σ goes as follows: the agent must always know what the next action prescribed by the program is and be able to perform it such that no matter what sensing output is obtained as a result of doing the action, she can continue this process with what remains of the program and, eventually, reach a configuration where she knows she can legally terminate. We can formalize this idea as follows. We define KHowEC(δ,σ) to be the smallest relation R(δ,σ) such that: