Agent-based target evaluation and fire doctrine: an aspect-oriented programming view

Threat evaluation is a vital process for any defense system, and it consists of a series of calculation and evaluation based on the inferred capabilities and intents of the targets that aim to give damage to defended assets. Target evaluation is proceeded in a wargame and the aim is to compare weapon target pairs according to a set of criteria. The target evaluation cycle is repeated anytime a new detection is received and when any change happens in the target currently detected. The whole process consists of a set of tasks that are shared between Command and Control units and the tasks require different responsibilities. Each task is succeeded by a specific behavior that is represented as a reasonably ordered set of actions. The task sharing is organized by taking the C2 architectures into account. In this paper, an agent-based command and control entity, which is in charge of target evaluation and giving engagement decision, is designed and it is situated in an air defense simulation environment. The study aims to propose an agent design in military decision-making domain, bringing analytic methods with the first-order logic together, and combine aspect orientation with agent design. The study also improves dynamic aspect management in agent programming using the relation concept.

Agile Tasking of Robotic Systems with Explicit Autonomy

Task agility is an increasingly desirable feature for robots in application domains such as manufacturing. The Canonical Robot Command Language (CRCL) is a lightweight information model built for agile tasking of robotic systems. CRCL replaces the underlying complex proprietary robot programming interface with a standard interface. In this paper, we exchange the automated planning component that CRCL used in the past for a rational agent in the Gwendolen agent programming language, thus providing greater possibilities for formal verification and explicit autonomy. We evaluate our approach by performing agile tasking in a kitting case study.

A Review of Agent-Based Programming for Multi-Agent Systems

Intelligent and autonomous agents is a subarea of symbolic artificial intelligence where these agents decide, either reactively or proactively, upon a course of action by reasoning about the information that is available about the world (including the environment, the agent itself, and other agents). It encompasses a multitude of techniques, such as negotiation protocols, agent simulation, multi-agent argumentation, multi-agent planning, and many others. In this paper, we focus on agent programming and we provide a systematic review of the literature in agent-based programming for multi-agent systems. In particular, we discuss both veteran (still maintained) and novel agent programming languages, their extensions, work on comparing some of these languages, and applications found in the literature that make use of agent programming.