Philippe Mathieu

ECAI Conference 2025 Conference Paper

Agent-Based Modeling of Context Effects in Consumer Choice

• Jarod Vanderlynden
• Philippe Mathieu
• Romain Warlop

This paper presents an agent-based model that explains three major context effects: decoy, similarity, and compromise effects, commonly observed in consumer decision-making. The model uses loss aversion theory, using a utility function that evaluates products relative to a reference point, defined by the average price and quality of all competing options. Agents are characterized by varying sensitivities to price and quality. Rather than forecasting exact consumer numbers, the model simulates relative preferences within a fixed population, making it a robust tool for analyzing market share dynamics. It accurately reproduces key behavioral phenomena and is calibrated using real-world retail data. Practical applications include price optimization and forecasting the impact of new product introductions. This framework offers a powerful yet focused tool for marketers seeking to understand and leverage consumers behaviors in competitive environments.

AAMAS Conference 2024 Conference Paper

Understanding the Impact of Promotions on Consumer Behavior

• Jarod Vanderlynden
• Philippe Mathieu
• Romain Warlop

Marketing is a complex tool companies use to publicize new products and build consumer loyalty. However, cost-effective understanding and prediction of marketing campaign influence on consumers’ behavior are necessary to maintain an effective business strategy. To understand the impact of the diversity of profiles and human behaviors, it is necessary to supplement aggregated solutions with the design of granular, individual-centered Agent-Based Models suitable for describing behavioral diversity. In this article, we propose a new model that reproduces customer loyalty as an emergent phenomenon while also demonstrating the effects of price wars on consumer loyalty. The model facilitates measuring the increase in sales during discounts, the drop in competitors’ sales, the negative effects of discount repetition and also complex phenomenon as decoy effect. Introducing a new product, a "decoy", in a competitive category can raise the sales of an existing product.

EAAI Journal 2013 Journal Article

Formalizing the construction of populations in multi-agent simulations

• Benoit Lacroix
• Philippe Mathieu
• Andras Kemeny

In individual-centered simulations, the variety and consistency of agents' behaviors reinforce the realism and validity of the simulation. Variety increases the diversity of behaviors that users meet during the simulation. Consistency ensures that these behaviors improve the users' feeling of immersion. In this work, we address the issue of the simultaneous influence of these two elements. We propose a formalization of the construction of populations for agent-based simulations, which provides the basis for a generic and non-intrusive tool allowing an out-of-the-agent design. First, the model uses behavioral patterns to describe standards of behaviors for the agents. They provide a behavioral archetype during agents' creation, and are also a compliance reference, that allows to detect deviant behaviors and address them. Then, a specific process instantiates the agents by using the specification provided by the patterns. Finally, inference enables to automate behavioral patterns configuration from real or simulated data. This formalization allows for the easy introduction of variety in agents' behaviors, while controlling the conformity to specifications. We applied the model to traffic simulation, in order to introduce driving styles specified using behavioral patterns (e. g. cautious or aggressive drivers). The behavioral realism of the traffic was therefore improved, and the experimentations we conducted show how the model contributes to increase the variety and the representativeness of the behaviors.

IJCAI Conference 2011 Conference Paper

An Interaction-Oriented Model for Multi-Scale Simulation

• S
• eacute; bastien Picault
• Philippe Mathieu

The design of multiagent simulations devoted to complex systems, addresses the issue of modeling behaviors that are involved at different space, time, behavior scales, each one being relevant so as to represent a feature of the phenomenon. We propose here a generic formalism intended to represent multiple environments, endowed with their own spatiotemporal scales and with behavioral rules for the agents they contain. An environment can be nested inside any agent, which itself is situated in one or more environments. This leads to a lattice decomposition of the global system, which appears to be necessary for an accurate design of multi-scale systems. This uniform representation of entities and behaviors at each abstraction level relies upon an interaction-oriented approach for the design of agent simulations, which clearly separates agents from interactions, from the modeling to the code. We also explain the implementation of our formalism within an existing interaction-based platform.

IROS Conference 2011 Conference Paper

Deterministic Kinodynamic Planning with hardware demonstrations

• François Gaillard
• Michaël Soulignac
• Cédric Dinont
• Philippe Mathieu

DKP (Deterministic Kinodynamic Planning) is a bottom-up trajectory planner for robots with flatness properties. DKP builds an exploration tree of which the branches are spline trajectories. DKP employs an A*-like algorithm to select which branch of the tree to grow. The selected trajectories are then grown in a propagation process which respects the kinematic constraints, such as linear/angular speed limits or obstacle avoidance. In addition, DKP produces trajectories that are immediately executable by the robot. Various experiments are provided to show the ability of DKP to effectively handle complex environments with one or more robots.

JAAMAS Journal 2011 Journal Article

IODA: an interaction-oriented approach for multi-agent based simulations

• Yoann Kubera
• Philippe Mathieu
• Sébastien Picault

Abstract Multi-Agent Systems (MAS) design methodologies and Integrated Development Environments exhibit many interesting properties that also support simulation design. Yet, in their current form, they are not appropriate enough to model Multi-Agent Based Simulations (MABS). Indeed, their design is focused on the functionalities to be achieved by the MAS and the allocation of these functionalities among software agents. In that context, the most important point of design is the organization of the agents and how they communicate with each other. On the opposite, MABS aim at studying emergent phenomena, the origin of which lies in the interactions between entities and their interaction with the environment. In that context, the interactions are not limited to exchanging messages but can also be fundamental physical interactions or any other actions involving simultaneously the environment and one or several agents. To deal with this issue, this paper presents the core notions of the Interaction-Oriented Design of Agent simulations ( IODA ) approach to simulation design. It includes a design methodology, a model, an architecture and also JEDI, a simple implementation of IODA concepts for reactive agents. First of all, our approach focuses on the design of an agent-independent specification of behaviors, called interactions. These interactions are not limited to the analysis phase of simulation: they are made concrete both in the model and at the implementation stage. In addition, no distinction is made between agents and objects: all entities of the simulation are agents. Owing to this principle, designing which interactions occur between agents, as well as how agents act, is achieved by means of an intuitive plug-and-play process, where interaction abilities are distributed among the agents. Besides, the guidelines provided by IODA are not limited to the specification of the model as they help the designer from the very beginning towards a concrete implementation of the simulation.

AAMAS Conference 2010 Conference Paper

Everything can be Agent!

• Yoann Kubera
• Philippe Mathieu
• S
• eacute; bastien Picault

Most Multi-Agent System designers use several notions - like "agent", "artifact", "object", etc. – to classify the entities involved in simulations. These notions require different methodologies, data structures and algorithms. In thispaper, we show that the representation of entities can befavorably unified. As a consequence, the design and implementation process are made easier, since the designer hasno longer to assign a fixed type to each entity during modelconstruction. The implementation handles entities throughan unified data structure and algorithm, and is thereforelightweight and more maintainable. Such an unification isperformed without efficiency loss in a concrete simulationmethodology called Ioda. According to common sense, wepropose to call such an unified entity simply "agent"!

ECAI Conference 2008 Conference Paper

Interaction-Oriented Agent Simulations: From Theory to Implementation

• Yoann Kubera
• Philippe Mathieu
• Sébastien Picault

This paper deals with the software architecture for individual-centered simulations, i. e. involving many entities interacting together. Many software architectures have been developped in this context, especially many advanced - but domain specific - frameworks. Yet those frameworks imply tight software dependencies between agents, behaviors and action selection mechanisms, which leads to many difficulties in modelling and programming. We propose a method and an architecture where interactions are reified regardless of agents, in order to obtain a complete interaction-oriented design process for simulations. Then, an agent is only an entity that can perform or undergo a set of interactions, even not specifically developped for it. Thus most interactions can be re-used in many contexts. In addition, our method clearly separates knowledge about behaviors from its processing, and thus makes the design of simulations easier. Moreover, this new and user-friendly approach helps programmers to build simulations with a large number of different behaviors at the same time, especially in the context of large-scale simulations.

AAMAS Conference 2006 Conference Paper

Artifacts for Time-Aware Agents

• Cedric Dinont
• Emmanuel Druon
• Philippe Mathieu
• Patrick Taillibert

ECAI Conference 2006 Conference Paper

Cheating Is Not Playing: Methodological Issues of Computational Game Theory

• Bruno Beaufils
• Philippe Mathieu

Computational Game Theory is a way to study and evaluate behaviors using game theory models, via agent-based computer simulations. One of the most known example of this approach is the famous Classical Iterated Prisoner's Dilemma (CIPD). It has been popularized by Axelrod in the beginning of the eighties and had led him to set up a successful Theory of Cooperation. This use of simulations has always been a challenging application of computer science, and of agent-based approaches, in particular to Social Sciences. It may be viewed as Empirical Game Theory. These kind of approach is often necessary since, in the general case, classical analytical ones do not give suitable results. These tools are also often used when full game-theoretic analysis is intractable. The usual method to evaluate behaviors consists in the collection of strategies, through open contests, and the confrontation of all of them as in a sport championship. Then it becomes, or at least seems to become, easy to evaluate and compare the efficiency of these behaviors. Evaluating strategies can however not be done efficiently without the insurance that algorithms used are well formed and that they can not introduce bias in their computation. It can not be done without tools able to prevent or, at least, measure deviation from the object of the study. Unfortunately people using such simulations often do not take care seriously about all those aspects, because they are not aware of it, and sometimes because they are. We will try to show effects of bad simulations practice on the simplest example. We show methodological issues which have to be taken care of, or avoided in order to prevent trouble in simulation results interpretation. Based on some simple illustration, we exhibit two kinds of bias that could be introduced. We classify them as voluntary or involuntary mistakes. The former ones can be explained by poor design of experimentations whereas the latter can defeat the purpose of the evaluation using simple ideas of agreement and cooperation. We also show the implications on interpretations and conclusions that such errors may produce. We state that scoring/ranking methods are part of the game, and as such have to be described with the game. Many points described may seem to be widely known. We think that with the growth of interest of such methods they have to be detailed and exposed clearly.

EUMAS Conference 2005 Conference Paper

Towards an Interaction-Based Design of Behaviors

• Philippe Mathieu
• Sébastien Picault

I&C Journal 2000 Journal Article

The Achievement of Knowledge Bases by Cycle Search

• Olivier Roussel
• Philippe Mathieu

Forward chaining is an algorithm that is particularly simple and therefore used in many inference systems. It computes the facts that are implied by a set of facts and rules. Unfortunately, this algorithm is not complete with respect to negation. To solve this problem, it is possible, in the context of propositional calculus, to automatically add the rules needed to make forward chaining complete. This transformation is a logical compilation of knowledge bases. This article presents a new method, based on a cycle search in a graph associated to the set of rules to compile, which allows a precise identification of what is needed for completeness.

LPAR Conference 1994 Conference Paper

A Kind of Achievement by Parts Method

• Philippe Mathieu
• Jean-Paul Delahaye

Abstract How to add new rules to a knowledge base Kb 1 to obtain a new knowledge base Kb 2 for which forward chaining on Kb 2 with any extensional knowledge base Ekb gives all the two-valued consequence literals of Kb 1 ∪ Ekb. We have shown in a previous paper that there exists such a method that we call Achievement. if (Kb 1 ∪ Ekb ) ⊨ L then L ∃ FwCh(Kb 2 ∪ Ekb ) with Kb 2 = Ach(Kb 1 ) Unfortunately these achievement methods have a great complexity in time and space which depends on the size of the initial knowledge base. Thus we try to achieve knowledge bases by parts to have a weaker complexity. Kb = Kb 1 ∪. .. ∪ Kb n, Ach( Kb ) = Ach(Kb 1 ) ∪. .. ∪ Ach( Kb n ) The aim of this paper is to give several methods to split knowledge bases in order to apply achievement by parts methods.

TCS Journal 1994 Journal Article

A kind of logical compilation for knowledge bases

• Philippe Mathieu
• Jean-Paul Delahaye

The forward chaining algorithm is perhaps the best-known algorithm in expert systems. However, it is not complete because it cannot compute the two-valued consequence literals of a propositional knowledge base (i. e. set of rules) with negations. If the user wants to compute them, he must use a particular algorithm, which often takes much time. We propose a compilation system for knowledge bases, which we call logical compilation, which allows us to compute the two-valued consequence literals of a knowledge base (i. e. set of rules) using a forward chaining on the compiled base with any extensional knowledge base (i. e. set of basic facts) added. We also use this compilation in a wide propositional calculus and solve the “or” problem in rule conclusion. We present several methods with their benefits to make this compilation and we give properties on knowledge bases to avoid this compilation. Finally, we give a theorem which defines incremental compilation.