Variable time scales, agent-based models, and role-playing games: The PIEPLUE river basin management game

This article presents a specific association of a role-playing game (RPG) and an agent-based model (ABM) aimed at dealing with a large range of time scales. Applications to the field of natural resource management lead one to consider the short time scale of resource use in practice at the same time as the longer ones related to resource dynamics or actors' investments. In their daily practice, stakeholders are translating their long-term strategies, a translation that is contextualized and combined with some cooccurring events. Long-term thinking is required for sustainable use of natural resources, but it should take into account its necessary adaptation on a short time scale. This raises the necessity for tools able to tackle jointly these various time scales. The similarity of architecture between computerized ABMs and RPGs makes them easy to associate in a hybrid tool, targeted at meeting this requirement. The proposition of this article is to allocate the representation of short time scales to computerized ABMs and the long ones to RPGs, while keeping the same static structural conceptual model, shared as a common root by both. This synergy is illustrated with PIEPLUE, an interactive setting tackling water-sharing issues.GESTION DE L'EAU;BASSIN VERSANT;RESSOURCE NATURELLE;MODELE;JEU DE ROLE;SYSTEME MULTIAGENTS;AGENT-BASED MODEL;CASE STUDY OF WATER SHARING;CONCEPTUAL MODEL;HYBRID TOOL;INVESTMENTS;LONG-TERM ISSUES;NATURAL RESOURCE MANAGEMENT;PIEPLUE;PARTICIPATORY MODELING;RESOURCE DYNAMICS;RESOURCE USE;ROLE-PLAYING GAME;STAKEHOLDERS;SUSTAINABLE USE OF NATURAL RESOURCES;TIME-SCALE DIVERSITY;VARIABLE TIME SCALES;WATER MANAGEMENT

Collaboration in the Semantic Grid: a Basis for e-Learning

The CoAKTinG project aims to advance the state of the art in collaborative mediated spaces for the Semantic Grid. This paper presents an overview of the hypertext and knowledge based tools which have been deployed to augment existing collaborative environments, and the ontology which is used to exchange structure, promote enhanced process tracking, and aid navigation of resources before, after, and while a collaboration occurs. While the primary focus of the project has been supporting e-Science, this paper also explores the similarities and application of CoAKTinG technologies as part of a human-centred design approach to e-Learning

Agents for educational games and simulations

This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications

Robust Spoken Language Understanding for House Service Robots

Service robotics has been growing significantly in thelast years, leading to several research results and to a numberof consumer products. One of the essential features of theserobotic platforms is represented by the ability of interactingwith users through natural language. Spoken commands canbe processed by a Spoken Language Understanding chain, inorder to obtain the desired behavior of the robot. The entrypoint of such a process is represented by an Automatic SpeechRecognition (ASR) module, that provides a list of transcriptionsfor a given spoken utterance. Although several well-performingASR engines are available off-the-shelf, they operate in a generalpurpose setting. Hence, they may be not well suited in therecognition of utterances given to robots in specific domains. Inthis work, we propose a practical yet robust strategy to re-ranklists of transcriptions. This approach improves the quality of ASRsystems in situated scenarios, i.e., the transcription of roboticcommands. The proposed method relies upon evidences derivedby a semantic grammar with semantic actions, designed tomodel typical commands expressed in scenarios that are specificto human service robotics. The outcomes obtained throughan experimental evaluation show that the approach is able toeffectively outperform the ASR baseline, obtained by selectingthe first transcription suggested by the AS