David Šišlák

A -globe: Agent Development Platform with Inaccessibility and Mobility Support

At present several Java-based multi-agent platforms from different developers are available, but none of them fully supports agent mobility and communication inaccessibility simulation. They are thus unsuitable for experiments with large scale real-world simulation. In this chapter we describe architecture of A-globe, fast, scalable and lightweight agent development platform with environmental simulation and mobility support. Beside the functions common to most agent platforms it provides a position-based messaging service, so it can be used for experiments with extensive environment simulation and communication inaccessibility. Simple benchmarks that compare the A-globe performance against other available agent platforms are also included.

Agent-Based Approach to Free-Flight Planning, Control, and Simulation

Intelligent-agents technology provides techniques and algorithms for distributed coordination and distributed decision making. The authors developed AgentFly, a multiagent prototype for air traffic control of free-flight-based operations of multiple aerial assets, based on intelligent agents. AgentFly provides mechanisms for distributed planning, negotiation-based collision avoidance, and multiagent flight simulation. The US Air Force supports this project, but the Federal Aviation Administration is also studying AgentFly for planning mixed traffic of manned and unmanned air traffic.

Agent-Based Cooperative Decentralized Airplane-Collision Avoidance

The efficiency of the current centralized air-traffic management is limited. A next-generation air transportation system should allow airplanes (manned and unmanned) to change their flight paths during the flight without approval from a centralized en route control. Such a scheme requires decentralized peer-to-peer conflict detection and collision-avoidance processes. In this paper, two cooperative (negotiation-based) conflict-resolution algorithms are presented: iterative peer-to-peer and multiparty algorithms. They are based on high-level flight-plan variations using evasion maneuvers. The algorithms work with a different level of coordination autonomy, respect realistic assumptions of imprecise flight execution (integrating required navigation performance), and work in real time, where the planning and plan-execution phases interleave. Both algorithms provide a resolution in a 4-D domain (3-D space and time). The proposed algorithms are evaluated experimentally, and their quality is studied in comparison with a state-of-the-art agent-based method-the satisficing game theory algorithm.

Autonomous agents for air-traffic deconfliction

This contribution presents a deployment exercise of multi-agent technology in the domain of deconflicted air-traffic control among several autonomous aerial vehicles (manned as well as unmanned). Negotiation based deconfliction algorithm have been developed and integrated in the agent-based model of the individual flight. Operation of the underlying multi-agent system has been integrated with freely available, geographical and tactical data sources in order to demonstrate openness of the technology. An additional, web client visualization and access component has been developed in order to facilitate a multi-user, platform independent use of the system. The features and application design is illustrated in the demonstration video clip.

A-Globe: Agent Platform with Inaccessibility and Mobility Support

At present several Java-based multi-agent platforms from different developers are available, but none of them fully supports agent mobility and communication inaccessibility. They are thus no suitable for experiments with real-world simulation. In this paper we describe architecture of newly developed agent platform A-GLOBE. It is fast and lightweight platform with agent mobility support. Beside the functions common to most of agent platforms it provides the Geographical Information System service to user, so it can be used for experiments with environment simulation and communication inaccessibility. A-GLOBE performance benchmarks compared against other agent platforms are also stated in this paper.

Agent-Based Multi-Layer Collision Avoidance to Unmanned Aerial Vehicles

This contribution presents a distributed, multi-layer collision avoidance architecture supporting efficient utilization of air space shared by several autonomous aerial vehicles. Presented multi-layer architecture is based on deliberative deployment of several collision avoidance methods by the aircraft at the same time. Both cooperative and non-cooperative collision avoidance methods are presented in the paper. The robustness of the architecture is justified by means of experimental validation of multi-agent simulation

AGENTFLY: Towards Multi-Agent Technology in Free Flight Air Traffic Control

Ever rising deployment of Unmanned Aerial Assets (UAAs) in complex military and rescue operations require novel and innovative methods for intelligent planning and collision avoidance among a high number of heterogeneous, semi-trusted flying assets in well specified and constrained areas [1]. We have studied the free flight concept as an alternative to the classical, centralized traffic control. In free flight the unmanned aerial assets are provided with flight trajectory that has been elaborated without consideration of other flying objects that may occupy the same air space. The collision threads are detected by each of the aircraft individually and the collisions are avoided by an asset-to-asset negotiation. Multi-agent technology is very well suited as a technological platform for supporting the free-flight concept among the heterogeneous UAAs. In this chapter we present AGENTFLY, multi-agent system for free-flight simulation and flexible collision avoidance.

Negotiation-Based Approach to Unmanned Aerial Vehicles

We present a framework for agent based aircraft deconfliction mechanism to enable efficient airspace use by various UAVs during coalition operations. In our approach, each vehicle is autonomous, but cooperative: it actively shares its flight plan with near aircrafts so that potential collisions can be detected and resolved using norm-based system. Non-cooperative and utility-based deconfliction approaches are also discussed as they offer a possibility to achieve more efficient and robust mechanism in the future. System is validated on multi-agent simulation that uses the public online-accessible data from various information sources

Distributed Platform for Large-Scale Agent-Based Simulations

We describe a distributed architecture for situated large-scale agent-based simulations with predominately local interactions. The approach, implemented in AglobeX Simulation platform, is based on a spatially partitioned simulated virtual environment and allocating a dedicated processing core to the environment simulation within each partition. In combination with dynamic load-balancing, such partitioning enables virtually unlimited scalability of the simulation platform. The approach has been used to extend the AgentFly air-traffic test-bed to support simulation of a complete civilian air-traffic touching National Air-Space of United States. Thorough evaluation of the system has been performed, confirming that it can scale up to a very high number of complex agents operating simultaneously (thousands of aircraft) and determining the impact of different configurations of the simulation architecture on its overall performance.

Multi-party Collision Avoidance among Unmanned Aerial Vehicles

This paper addresses the problem of distributed cooperative collision avoidance that supports efficient utilization of air space shared by several autonomous unmanned aerial vehicles. The novel multi-party collision avoidance (MPCA) algorithm is described. It is compared to the iterative peer-to-peer collision avoidance (IPPCA) algorithm that iteratively optimizes social welfare. The paper provides a set of experiments and a comparison of different collision avoidance mechanisms in a multi-agent model of air traffic.This paper addresses the problem of distributed cooperative collision avoidance that supports efficient utilization of air space shared by several autonomous unmanned aerial vehicles. The novel multi-party collision avoidance (MPCA) algorithm is described. It is compared to the iterative peer-to-peer collision avoidance (IPPCA) algorithm that iteratively optimizes social welfare. The paper provides a set of experiments and a comparison of different collision avoidance mechanisms in a multi-agent model of air traffic.