Social Reasoning in Computational Multi-Agent Systems

The concept of multi-agent system contributes to the fields of computer science and artificial intelligence by a societal and distributed approach to computing. Non-trivial problems can be solved, complex systems can simulated and controlled by a community of autonomous computational entities. These entities can be geographically distributed across wider network infrastructures. The computational entities in multi-agent systems need to perform specific types of social interaction in order to achieve collective behavior and collective decision making. Socially oriented reasoning, the reasoning process that underlies rational interaction, is currently a subject of a deeper theoretical investigation and practical deployment in industrial applications. This habilitation thesis provides an introduction to the field of multi-agent systems, required knowledge of a formal system for reasoning about an agent and a unified view on agents ’ social knowledge and reasoning processes maintaining validity and accurateness of social knowledge. In this thesis we present three principal approaches to handling agents social knowledge: the acquaintance model, stand-in agents and meta-agents. Experiments with socially oriented behavior and comments on practical applicability of the socially oriented reasoning in practical situations are presented also in the thesis. Souhrn: Koncept multi-agentních systém˚u pˇrispívá do počítačov´ych věd a umělé inteligence distribuovan´ym a na sociálním uvaˇzování zaloˇzen´ym pˇrístupem. Netriviální problémy lze ˇreˇsit, komplexní systémy lze simulovat a ˇrídit pomocí komunity autonomních v´ypočetních jednotek. Tyto jednotky mohou b´yt geograficky distribuované napˇríč ˇsirokou počítačovou sítí. Autonomní v´ypočetní jednotky v multi-agentních systémech vykonávají specifické typy sociální interakce za účelem dosaˇzení kolektivního chování a společného rozhodování. Model sociálníh

Bi-objective maritime route planning in pirate-infested waters

Contemporary maritime shipping is subject to a large number of constraints given by tight shipping schedules and very low margins. Additionally, problematic areas with increased security needs dynamically changing in time, combined with seasonal oceanographic and meteorological conditions pose a challenging voyage planning problem. In this work we present a risk-aware voyage planner taking into account spatio-temporal environmental conditions. The planner is based on a graph-based search algorithm A* . We discretize the required area into a graph, we store various layers of information into the edges of the graph (such as risk and weather conditions) in a form of numeric weights and we define a bi-objective planning problem with a tradeoff between security and duration of the voyage. The nature of the algorithm guarantees a complete and optimal solution in a form of an optimized voyage with respect to the criterion function composed of the two weighted components, i.e, duration and security of the voyage. We demonstrate the approach on our area of interest: Indian Ocean. We use NATO piracy activity risk surface as the risk layer and we compute all transit voyages between relevant routing points in the area. Finally, thanks to the discretization of the problem, we are able to integrate corridors imposed by the shipping authorities and evaluate additional what-if scenarios with extended corridor systems. The resulting planner is exposed to the public using a web service with an easy interface requiring start time of the voyage and the origin and the destination point of voyage. Combined with an expressive visualization, this tool demonstrates the capabilities of the proposed solution

Agent-based approach to illegal maritime behavior modeling

Maritime shipping is a set of complex activities with a large number of actors involved. We focus on a subset of illegal maritime activities, such as armed robberies, maritime piracy or contraband smuggling. To fight against them and minimize their negative impact naval authorities typically introduce a number of countermeasures, such as deployed patrols or surveillance agents. Due to very high costs of countermeasures it is often beneficial to evaluate their impact using a simulation, allowing what-if analysis and evaluation of a range of scenarios before actually deploying the countermeasures. We introduce BANDIT, an agent-based computational platform, which is designed to evaluate scenarios with an accent on the modeling of different types of illegal behavior and on the interaction between agents. The platform consists of an agent behavior modeling system and a multi-agent maritime simulator. The platform allows the definition of a number of scenarios through a simple configuration and it offers the means to run these scenarios in a single or a batch mode and evaluate the results as single or aggregate data sets respectively. We demonstrate the usefulness of the platform on the scenarios of the drug smuggling problem in the seas surrounding Central America. Senario outcomes (e.g., heatmaps of activities, set of trajectories etc.) are subsequently used to help with the design of effective countermeasures, i.e., allocating naval patrols and planning their patrol routes

Globally asynchronous locally synchronous FPGA architectures

Abstract. Globally Asynchronous Locally Synchronous (GALS) Systems have provoked renewed interest over recent years as they have the potential to combine the benefits of asynchronous and synchronous design paradigms. It has been applied to ASICs, but not yet applied to FPGAs. In this paper we propose applying GALS techniques to FPGAs in order to overcome the limitation on timing imposed by slow routing.