Jean-Sébastien Monzani

Using an intermediate skeleton and inverse kinematics for motion retargeting

In this paper, we present a new method for solving the Motion Retargeting Problem, by using an intermediate skeleton. This allows us to convert movements between hierarchically and geometrically different characters. An Inverse Kinematics engine is then used to enforce Cartesian constraints while staying as close as possible to the captured motion.

Integrating behavioural animation techniques

Our research focuses on animating autonomous virtual humans which are able to take decisions by themselves. We especially address in this paper the technical problem of integrating altogether the physical simulation of agents (represented as virtual humans in a 3D environment) and their behaviours and motivations, driven by a Beliefs, Desires and Intentions architecture. We also explain how goals drive plans, and how an agent can coherently handle concurrent tasks.

Negotiation in Technology Landscapes: An Actor-Issue Analysis

In large-scale negotiation problems and in assessments of complex and uncertain environments, it is vital to analyze the different stakeholders involved and to evaluate their positions in the negotiations. This paper extends a model, which merges previous multi-issue and actor-focused methods, based on power relationships between stakeholders and their ability to bargain in order to increase their utility. The model has already used for assessing a public WLAN landscape. The paper emphasizes the dynamic application of the model we developed for experimenting the negotiation evolution, shifting positions on some issues, and exchanging positions between actors. We also claim that such forecasting analyses of negotiation landscapes can be significantly improved using more appropriate visualization support. We propose new visualization tools for analyzing negotiation outcomes, representing negotiation landscapes, and applying what-if simulations, using passive influence, expected outcome and dissatisfaction, power distribution, proximity, and negotiation maps.

ACE: A Platform for the Real Time Simulation of Virtual Human Agents

The paper describes a system platform for virtual human agent simulations that is able to coherently manage the shared virtual environment. Our “agent common environment” (ACE) provides built-in commands for perception and for acting, while the in-between step of reasoning and behavior computation is defined through an external, extendible, and parameterized collection of behavioral plug-ins. Such plug-ins are of two types: the first type defines agent-object interactivity by using a feature modeling approach, and the second type controls the reasoning and behavior of each agent through scripted modules. The system is analyzed and a simulation example integrating some modules with a Lisp behavioral system is shown

Decision and visualization for negotiation

We present a new strategic model for solving large scale problems involving numerous actors and issues. It merges previous multi-issues and actors methods based on power relationship between stakeholders and their ability to bargain in order to increase their utility. We apply new visualization techniques to analyse its outputs: dissatisfaction analysis, proximity map, passive influences and power repartition on issues. We simultaneously describe the implemented system on an assessment in the wireless Internet service provider scenario.

Verbal communication: using approximate sound propagation to design an inter-agents communication language

We present a method for generating conversations between human-like agents by proposing specific parameters for inter-agents messages with an approximation of virtual sound propagation. We are then be able to simulate appropriate human-like behaviours automatically. For instance, we demonstrate how to create proper reactions for agents that are not able to understand, but only to hear the sentences

Communicative Autonomous Agents

We present a way to mix the lower control of agents with the high level specifications of their goals. This paper addresses various topics required to animate virtual humans in a distributed way such as combining primary actions into tasks, using verbal communication between virtual humans and directing them with high level orders. Our models have been tested into a multi-languages / multi-modules application as described below.