Concerning a software tool of legal reasoning, it is important to describe the prediction about the result of a criminal action, because a crime is often caused by the unpredictability of the result of the defendant. In the court, the judge needs to investigate the predictability and the intention of the agent. Previously, we have formalized the reasoning process of judgment by action model in dynamic epistemic logic (DEL) and have attempted to describe the precedents. However, the prediction in legal cases depends not only on the states of knowledge but also on the limited degree of attention by agents. In this paper, we employ DEL with awareness for multi-agent to represent the predictability and model the typical criminal precedents. We propose a revised semantics of action model with awareness which can define each basic action model to reproduce the agent’s considering process. To describe the legal reasoning we introduce an extension of modeling program DEMO to include the awareness (we call it DEMO[Formula: see text]) and present a GUI in this extended program to calculate the updated epistemic model easily and to classify precedents according to the degree of prediction. In the end, we calculate the epistemic models of typical criminal precedents by this newly developed tool and estimate them.
When we study multi-agent communication system, it forces us to manage an existence of communication channels between agents, such as phone numbers or e-mail addresses, while ordinary modal logic for multiagent system does not consider the notion of channel. This paper proposes a decidable and semantically complete logic of belief with communication channels, and then expands the logic with informing action operators to change agents' beliefs via communication channels. Moreover, for a better formalism for handling these semantics efficiently, we propose a linear algebraic representation of these. That is, with the help of Fitting (2003) and van Benthem and Liu (2007), we reformulate our proposed semantics of the doxastic static logic and its dynamic extensions in terms of boolean matrices. We also implement and publicize a calculation system of our matrix reformulations as an open system on the web.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.