Verifying Time and Communication Costs of Rule-Based Reasoners

Automated Verification of Resource Requirements in Multi-Agent Systems Using Abstraction

“…To illustrate the scalability of our approach we implemented an example scenario reported in [9]. In this scenario, a system of communicating reasoners attempt to solve a (synthetic) distributed reasoning problem in which the set of rules and facts that describes agents' knowledge base are constructed from a complete binary tree.…”

“…For compatibility with the propositional example considered in [9], we assume that the variable x is substituted by a single constant value 'a', and the goal is to derive D 1 (a). One can easily see that a larger system can be generated using 16 'leaf' facts A 1 (x), .…”

“…Such generic distributed reasoning problems can be easily parameterised by the number of leaf facts and the distribution of facts and rules among the agents. In [9], the results of experiments on such problems using the Mocha model-checker [6] are reported. In the simplest case of a single agent, the largest problem that could be verified using Mocha had 128 leaf facts.…”

“…However, using our tool we are able to verify a system with 2048 leaf facts. The experimental results are summarised in Table 1 In case of a multi-agent systems, the exchange of information between agents was modelled as an abstract Copy operation in [9]. Each copy operation takes one tick of system time and does not require any special communication rules.…”

“…Abstract specifications are given as LTL formulas which describe the external behaviour of agents, and allow their temporal behaviour (the response time behaviour of the agent), to be compactly modelled. We illustrate the scalability of our approach by comparing it to results presented in [9] for a synthetic distributed reasoning problem, and presenting results for a more complex multi-agent reasoning example.…”