## No full-text available

To read the full-text of this research,

you can request a copy directly from the authors.

To read the full-text of this research,

you can request a copy directly from the authors.

ResearchGate has not been able to resolve any citations for this publication.

ACL2 allows users to define predicates whose logical behavior mimics that of universally or existentially quantified formulae. Proof support for such quantification, however, is quite limited. We present an ACL2 framework that employs tables, computed hints and clause processing to identify quantified formulae and to skolemize or instantiate them when possible. We demonstrate how the framework can be used to prove automatically the forall-p-append example presented in the ACL2 documentation.

We describe an ACL2 package for defining partial recursive functions that
also supports efficient execution. While packages for defining partial
recursive functions already exist for other theorem provers, they often require
inductive definitions or recursion operators which are not available in ACL2
and they provide little, if any, support for executing the resulting
definitions. We use step-indexing as the underlying implementation technology,
enabling the definitions to be carried out in first order logic. We also show
how recent enhancements to ACL2's guard feature can be used to enable the
efficient execution of partial recursive functions.

This paper poses the cooperative perimeter-surveillance problem and offers a decentralized solution that accounts for perimeter growth (expanding or contracting) and insertion/deletion of team members. By identifying and sharing the critical coordination information and by exploiting the known communication topology, only a small communication range is required for accurate performance. Simulation and hardware results are presented that demonstrate the applicability of the solution.

Designing protocols for multi-agent interaction that achieve the desired behavior is a challenging and error-prone process. The standard practice is to manually develop proofs of protocol correctness that rely on human intuition and require significant effort to develop. Even then, proofs can have mistakes that may go unnoticed after peer review, modeling and simulation, and testing. The use of formal methods can reduce the potential for such errors. In this paper, we discuss our experience applying model checking to a previously published multi-agent protocol for unmanned air vehicles. The original publication provides a compelling proof of correctness, along with extensive simulation results to support it. However, analysis through model checking found an error in one of the proof’s main lemmas. In this paper, we start by providing an overview of the protocol and its original “proof” of correctness, which represents the standard practice in multi-agent protocol design. We then describe how we modeled the protocol for a three-vehicle system in a model checker, the counterexample it returned, and the insight this counterexample provided. We also discuss benefits, limitations, and lessons learned from this exercise, as well as what future efforts would be needed to fully verify the protocol for an arbitrary number of vehicles.