A5083410100- Bayesian Modeling and Causal Inference
- Multi-Criteria Decision Making
- Logic, Reasoning, and Knowledge
- Reinforcement Learning in Robotics
- Plant and animal studies
- Forest Management and Policy
- Game Theory and Applications
- Ecology and Vegetation Dynamics Studies
- Machine Learning and Algorithms
- Species Distribution and Climate Change
- French Urban and Social Studies
- Economic and Environmental Valuation
- Game Theory and Voting Systems
- AI-based Problem Solving and Planning
- Decision-Making and Behavioral Economics
- Weed Control and Herbicide Applications
- Agriculture and Rural Development Research
- Rough Sets and Fuzzy Logic
- Social Sciences and Governance
- Formal Methods in Verification
- Sustainability and Ecological Systems Analysis
- Semantic Web and Ontologies
- Land Use and Ecosystem Services
- Plant Pathogens and Resistance
- Auction Theory and Applications
Mathématiques et Informatique Appliquées
2015-2024
Département Mathématiques et Informatique Appliquées
2015-2024
Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement
2003-2024
Génétique Physiologie et Systèmes d'Elevage
2021-2022
Université de Toulouse
2017-2022
Institut National de la Recherche Agronomique
2002-2021
Université Toulouse III - Paul Sabatier
1998-2013
Institut de Recherche en Informatique de Toulouse
1998-2013
Biopolymères Interactions Assemblages
2007
The Dialogue
2000
Stochastic dynamic programming (SDP) or Markov decision processes (MDP) are increasingly being used in ecology to find the best decisions over time and under uncertainty so that chance of achieving an objective is maximised. To date, few programs available solve SDP/MDP. We present MDPtoolbox, a multi‐platform set functions problems (MATLAB, GNU Octave, Scilab R). MDPtoolbox provides state‐of‐the‐art ready use algorithms wide range MDPs. easy use, freely has been continuously improved since...
Food-web theory can be a powerful guide to the management of complex ecosystems. However, we show that indices species importance common in food-web and network poor ecosystem management, resulting significantly more extinctions than necessary. We use Bayesian Networks Constrained Combinatorial Optimization find optimal strategies for wide range real hypothetical food webs. This Artificial Intelligence approach provides ability test performance any index prioritizing network. While no single...
In conservation biology and natural resource management, adaptive management is an iterative process of improving by reducing uncertainty via monitoring. Adaptive the principal tool for conserving endangered species under global change, yet problems suffer from a poor suite solution methods. The common approach used to solve problem assume system state known dynamics can be one set pre-defined models. method unsatisfactory, employing value iteration on discretized belief MDP which restricts...
An overview of the use discrete Sugeno integral as either an aggregation tool or a preference functional is presented in qualitative framework two decision paradigms: multi-criteria decision-making and under uncertainty. The parallelism between representation theorems both settings stressed, even if basic requirement like idempotency scheme should be explicitely stated decision-making, while its counterpart implicit uncertainty by equating utility constant act with consequence. Important...
Abstract Confronted by significant impacts to ecosystems world‐wide, decision makers face the challenge of maintaining both biodiversity and provision ecosystem services ( ES ). However, objectives managing supplying may not always be in concert, resulting need for trade‐offs. Understanding these potential trade‐offs is crucial identifying circumstances under which conservation strategies designed maximise either or will result win‐win win‐lose outcomes. One important factor that influence...
Control theory plays a pivotal role in understanding and optimizing the behavior of complex dynamical systems across various scientific engineering disciplines. Two key frameworks that have emerged for modeling solving control problems stochastic are piecewise deterministic Markov processes (PDMPs) decision (MDPs). Each framework has its unique strengths, their intersection offers promising opportunities tackling broad class problems, particularly context impulse controls decision-making...
This paper describes a logical machinery for computing decisions, where the available knowledge on state of world is described by possibilistic propositional logic base (i.e., collection statements associated with qualitative c
Predicting the population dynamics of annual plants is a challenge due to their hidden seed banks in field. However, such predictions are highly valuable for determining management strategies, specifically agricultural landscapes. In agroecosystems, most weed seeds survive during unfavourable seasons and persist several years bank. This causes difficulties making accurate life history traits (LHT). Consequently, it very difficult identify strategies that limit both populations species...
Abstract Ecological systems are made up of complex and often unknown interactions feedbacks. Uncovering these feedbacks among species, ecosystem functions, services is challenging, costly, time-consuming. Here, we ask: for which features does resolving the uncertainty about from function to species improve management outcomes? We develop a dynamic value information analysis risk-neutral risk-prone managers on motif ecosystems explore influence five ecological features. find that learning not...