Commercial software tools for intelligent autonomous systems

This article identifies some of the commercial software tools that can potentially be examined, or relied upon for their techniques, within new EPSRC projects entitled "Reconfigurable Autonomy" and "Distributed Sensing and Control.." awarded and to be undertaken between Liverpool, Southampton and Surrey Universities in the next 4 years. Although such projects strive to produce new techniques of various kinds, the software reviewed here could also influence, shape and help to integrate the algorithmic outcome of all 16 projects awarded within the EPSRC Autonomous and Intelligent Systems programme early 2012. To avoid mis-representation of technololgies provided by the software producer companies listed, most of this review is based on using quotes from original product descriptions

Probabilistic Perception Revision in AgentSpeak(L)

Agent programming is mostly a symbolic discipline and, as such, draws little benefits from probabilistic areas as machine learning and graphical models. However, the greatest objective of agent research is the achievement of autonomy in dynamical and complex environments — a goal that implies embracing uncertainty and therefore the entailed representations, algorithms and techniques. This paper proposes an innovative and conflict free two layer approach to agent programming that uses already established methods and tools from both symbolic and probabilistic artificial intelligence. Moreover, this method is illustrated by means of a widely used agent programming example, GOLDMINERS

An Analysis of the Insertion of Virtual Players in GMABS Methodology Using the Vip-JogoMan Prototype

The GMABS (Games and Multi-Agent-Based Simulation) methodology was created from the integration of RPG and MABS techniques. This methodology links the dynamic capacity of MABS (Multi-Agent-Based Simulation) and the discussion and learning capacity of RPG (Role-Playing Games). Using GMABS, we have developed two prototypes in the natural resources management domain. The first prototype, called JogoMan (Adamatti et. al, 2005), is a paper-based game: all players need to be physically present in the same place and time, and there is a minimum needed number of participants to play the game. In order to avoid this constraint, we have built a second prototype, called ViP-JogoMan (Adamatti et. al, 2007), which is an extension of the first one. This second game enables the insertion of virtual players that can substitute some real players in the game. These virtual players can partially mime real behaviors and capture autonomy, social abilities, reaction and adaptation of the real players. We have chosen the BDI architecture to model these virtual players, since its paradigm is based on folk psychology; hence, its core concepts easily map the language that people use to describe their reasoning and actions in everyday life. ViP-JogoMan is a computer-based game, in which people play via Web, players can be in different places and it does not have a hard constraint regarding the minimum number of real players. Our aim in this paper is to present some test results obtained with both prototypes, as well as to present a preliminary discussion on how the insertion of virtual players has affected the game results.Role-Playing Games, Multi-Agent Based Simulation, Natural Resources, Virtual Players

Agents and Robots for Reliable Engineered Autonomy

This book contains the contributions of the Special Issue entitled "Agents and Robots for Reliable Engineered Autonomy". The Special Issue was based on the successful first edition of the "Workshop on Agents and Robots for reliable Engineered Autonomy" (AREA 2020), co-located with the 24th European Conference on Artificial Intelligence (ECAI 2020). The aim was to bring together researchers from autonomous agents, as well as software engineering and robotics communities, as combining knowledge from these three research areas may lead to innovative approaches that solve complex problems related to the verification and validation of autonomous robotic systems

A Review of Platforms for the Development of Agent Systems

Agent-based computing is an active field of research with the goal of building autonomous software of hardware entities. This task is often facilitated by the use of dedicated, specialized frameworks. For almost thirty years, many such agent platforms have been developed. Meanwhile, some of them have been abandoned, others continue their development and new platforms are released. This paper presents a up-to-date review of the existing agent platforms and also a historical perspective of this domain. It aims to serve as a reference point for people interested in developing agent systems. This work details the main characteristics of the included agent platforms, together with links to specific projects where they have been used. It distinguishes between the active platforms and those no longer under development or with unclear status. It also classifies the agent platforms as general purpose ones, free or commercial, and specialized ones, which can be used for particular types of applications.Comment: 40 pages, 2 figures, 9 tables, 83 reference

Prototypes of productivity tools for the jadescript programming language

Jadescript is an agent-oriented programming language built on top of JADE. So far, the focus of the development of the language was on design choices, on syntax refinements, and on the introduction of expressions and constructs for agent-related abstractions and tasks. In this paper, a proposal to achieve the crucial goal of making Jadescript suitable for professional use is presented. The success of Jadescript, as a solid language to build real-world agent-based software systems, is necessarily related to its effective integration with mainstream development tools. In this paper, some of the productivity tools developed to integrate Jadescript with a mainstream development environment are presented as a way to promote the successful adoption of the language towards the community of JADE users

Affect and believability in game characters:a review of the use of affective computing in games

Virtual agents are important in many digital environments. Designing a character that highly engages users in terms of interaction is an intricate task constrained by many requirements. One aspect that has gained more attention recently is the effective dimension of the agent. Several studies have addressed the possibility of developing an affect-aware system for a better user experience. Particularly in games, including emotional and social features in NPCs adds depth to the characters, enriches interaction possibilities, and combined with the basic level of competence, creates a more appealing game. Design requirements for emotionally intelligent NPCs differ from general autonomous agents with the main goal being a stronger player-agent relationship as opposed to problem solving and goal assessment. Nevertheless, deploying an affective module into NPCs adds to the complexity of the architecture and constraints. In addition, using such composite NPC in games seems beyond current technology, despite some brave attempts. However, a MARPO-type modular architecture would seem a useful starting point for adding emotions

ReSpecTX: Programming Interaction Made Easy

In this paper we present the ReSpecTX language, toolchain, and standard library as a first step of a path aimed at closing the gap between coordination languages \u2013 mostly a prerogative of the academic realm until now \u2013 and their industrial counterparts. Since the limited adoption of coordination languages within the industrial realm is also due to the lack of suitable toolchains and libraries of reusable mechanisms, ReSpecTX equips a core coordination language (ReSpecT) with tools and features commonly found in mainstream programming languages. In particular, ReSpecTX makes it possible to provide a reference library of reusable and composable interaction patterns

A multi level explainability framework for BDI Multi Agent Systems

As software systems become more complex and the level of abstraction increases, programming and understanding behaviour become more difficult. This is particularly evident in autonomous systems that need to be resilient to change and adapt to possibly unexpected problems, as there are not yet mature tools for managing understanding. A complete understanding of the system is indispensable at every stage of software development, starting with the initial requirements analysis by experts in the field, through to development, implementation, debugging, testing, and product validation. A common and valid approach to increasing understandability in the field of Explainable AI is to provide explanations that can convey the decision making processes and the motivations behind the choices made by the system. Motivated by the different use cases of the explanation and the different classes of target users, it is necessary to deal with different levels of abstraction in the generated explanations since they target specific classes of users with different requirements and goals. This thesis introduces the idea of multi-level explainability as a way to generate different explanations for the same systems at different levels of detail. A low-level explanation related to detailed code could help developers in the debugging and testing phases, while a high-level explanation could support domain experts and designers or contribute to the validation phase to align the system with the requirements. The model taken as a reference for the automatic generation of explanations is the BDI (Belief-Desire-Intention) model, as it would be easier for humans to understand the mentalistic explanation of a system that behaves rationally given its desires and current beliefs. In this work we have prototyped an explainability tool for BDI agents and multi-agent systems that deals with multiple levels of abstraction that can be used for different purposes by different classes of users