Programming with Conditionals: Epistemic Programming for Scientific Discovery

In order to provide scientists with a computational methodology and some computational tools to program their epistemic processes in scientific discovery, we are establishing a novel programming paradigm, named ‘Epistemic Programming’, which regards conditionals as the subject of computing, takes primary epistemic operations as basic operations of computing, and regards epistemic processes as the subject of programming. This paper presents our fundamental observations and assumptions on scientific discovery processes and their automation, research problems on modeling, automating, and programming epistemic processes, and an outline of our research project of Epistemic Programming.

Model Checking for Probabilistic Multiagent Systems

In multiagent systems,agents usually do not have complete information of the whole system,which makes the analysis of such systems hard.The incompleteness of information is normally modelled by means of accessibility relations,and the schedulers consistent with such relations are called uniform.In this paper,we consider probabilistic multiagent systems with accessibility relations and focus on the model checking problem with respect to the probabilistic epistemic temporal logic,which can specify both temporal and epistemic properties.However,the problem is undecidable in general.We show that it becomes decidable when restricted to memoryless uniform schedulers.Then,we present two algorithms for this case:one reduces the model checking problem into a mixed integer non-linear programming(MINLP)problem,which can then be solved by Satisfiability Modulo Theories(SMT)solvers,and the other is an approximate algorithm based on the upper confidence bounds applied to trees(UCT)algorithm,which can return a result whenever queried.These algorithms have been implemented in an existing model checker and then validated on experiments.The experimental results show the efficiency and extendability of these algorithms,and the algorithm based on UCT outperforms the one based on MINLP in most cases.

Knowledge structure approach to verification of authentication protocols

The standard Kripke semantics of epistemic logics has been applied successfully to reasoning communication protocols under the assumption that the network is not hostile. This paper introduces a natural semantics of Kripke semantics called knowledge structure and, by this kind of Kripke semantics, analyzes communication protocols over hostile networks, especially on authentication protocols. Compared with BAN-like logics, the method is automatically implementable because it operates on the actual definitions of the protocols, not on some difficult-to-establish justifications of them. What is more, the corresponding tool called SPV (Security Protocol Verifier) has been developed. Another salient point of this approach is that it is justification-oriented instead of falsification-oriented, i.e. finding bugs in protocols.

Abstraction for model checking multi-agent systems

Model checking multi-agent systems （MAS） always suffers from the state explosion problem. In this paper we focus on an abstraction technique which is one of the major methods for overcoming this problem. For a multi-agent system, we present a novel abstraction procedure which reduces the state space by collapsing the global states in the system. The abstraction is automatically computed according to the property to be verified. The resulting abstract system simulates the concrete system, while the universal temporal epistemic properties are preserved. Our abstraction is an over-approximation. If some universal temporal epistemic property is not satisfied, then we need to identify spurious counterexamples. We further show how to reduce complex counterexamples to simple structures, i.e., paths and loops, such that the counterexamples can be checked and the abstraction can be refined efficiently. Finally, we illustrate the abstraction technique with a card game.