Hamidou Tembine

Although valued for its ability to allow teams to collaborate and foster coalitional behaviors among the participants, game theory’s application to networking systems is not without challenges. Distributed Strategic Learning for Wireless Engineers illuminates the promise of learning in dynamic games as a tool for analyzing network evolution and und...

This paper presents an interplay between deep learning and game theory. It models basic deep learning tasks as strategic games. Then, distributionally robust games and their relationship with deep generative adversarial networks (GANs) are presented. To achieve a higher order convergence rate without using a second derivative of the objective funct...

This paper studies blockchain cryptographic tokens by means of mean-field-type game theory. It introduces variance-aware utility function per decision-maker to capture the risk of cryptographic tokens associated with the uncertainties of technology adoption, network security, regulatory legislation and market volatility. A relationship between netw...

Dive into the fascinating world of Artificial Intelligence with "Machine Intelligence in Africa: 20 Questions". This captivating book takes you on a journey to the heart of this technological revolution that is shaping our future, even in the remote corners of African landscapes. Explore crucial questions about data privacy, the accountability of m...

Book on mean-field-type games (under preparation)

By reading this Timadie report, you will discover how Mean-Field-Type Game Theory sheds light on the complex interactions among the inhabitants of the Dogon Country, revealing fascinating dynamics and surprising strategies. Explore the unique economic sectors of Dogon Country: Uncover the mysteries of cereal farming during the rainy season, immerse...

Over the past four years, we have witnessed a true technological revolution in Africa, with the emergence of x-chains developed by Timadie. These blockchain-inspired platforms have opened up new possibilities in key areas such as agriculture, information, livestock, and women's empowerment. They have brought innovative solutions to the challenges A...

The emergence of Multimodal Large Learning Models (MLLMs) is transforming the field of strategic learning and machine intelligence, enabling machines to comprehend up to various levels and generate content across various modalities, including text, images, audios, sounds, videos, music, gestures, sensors, emotions, voices, Infrared-Table-Time serie...

This Timadie report explores vast possibilities of Machine Intelligence for defense and security. You will discover how these technologies are transforming our approach to threat prevention, infrastructure protection, and the preservation of our society's security. Machine Intelligence will continue to evolve at a rapid pace, opening new perspectiv...

We are all familiar with those frustrating moments when our road trip turns into a slow crawl, stuck in an endless stream of immobile vehicles. These despair-inducing situations, known as traffic jams, sometimes seem to appear out of nowhere, defying apparent logic. Yet, behind these mysterious phenomena, complex and intriguing mechanisms are at pl...

We investigate the concept of Strategic Generative AI, where multiple agents engage in interactions. Each agent is equipped with its own generative AI system, enabling them to acquire knowledge, adapt, and make decisions while factoring in various elements such as risk, the decisions of other agents, and the resulting outcomes. This naturally gives...

We study the control design for a clinical positive-pressure ventilation device. We present a non-linear and linearized models of the positive-pressure ventilator, which are validated by means of clinical tests performed with four human patients. We propose a unified stochastic differential equation (SDE) with switching-regime-dependent drift and d...

This study addresses primal–dual dynamics for a stochastic programming problem for capacity network design. It is proven that consensus can be achieved on the here and now variables which represent the capacity of the network. The main contribution is a heuristic approach which involves the formulation of the problem as a mean-field game. Every age...

This paper studies fishery strategies in lakes, seas, and shallow rivers subject to agricultural and industrial pollution. The flowing pollutants are modeled by a nonlinear differential equation in a general manner. The logistic growth model for the fish population is modified to cover the pollution impact on the fish growth rate. We start by prese...

We study a risk-aware multi-level evacuation control problem considering smoke propagation. We propose a continuous-time Markov-chain-based modeling for both population motion and smoke propagation while considering spatial/physical constraints such as walls and/or obstacles. Besides, we formally present some properties of the evacuation model. To...

This paper solves a mean-field type hierarchical optimal control problem in electricity market. The authors consider n − 1 prosumers and one producer. The ith prosumer, for 1 < i < n, is a leader of the (i − 1)th prosumer and is a follower of the (i + 1)th prosumer. The first player (agent) is the follower at the bottom whereas the nth is the leade...

In this paper we present an age-and-migration-dependent Markov-chain-based model for the propagation of the COVID-19, together with a user-friendly MatLab-based toolbox. We present several examples to estimate the propagation of the virus worldwide and in a particular country.

In this article, a profit optimization between electricity producers is formulated and solved. The problem is described by a linear jump-diffusion system of conditional mean-field type where the conditioning is with respect to common noise and a quadratic cost functional involving the second moment, the square of the conditional expectation of the...

In this article, a class of mean-field-type games with discrete-continuous state spaces is considered. We establish Bellman systems which provide sufficiency conditions for mean-field-type equilibria in state-and-mean-field-type feedback form. We then derive unnormalized master adjoint systems (MASS). The methodology is shown to be flexible enough...

Strategic modelling with a panoramic view plays an important role in decision-making problems. It offers the possibility of generating different solutions before making a decision. This is particularly relevant in critical situations. This article addresses the problem of allocating resources, whether financial, material or human, so that it is opt...

This paper presents a tutorial of the role that mean-field-type games play in the design of risk-aware controllers. The tutorial is presented in an easy-to-follow manner for beginners, engineers and early-career scientists. It starts by introducing a basic stochastic mean-field-free control design problem and progressively adds more complexity to t...

Multi-access edge computing (MEC) has been proposed to reduce latency inherent in traditional cloud computing. One of the services offered in an MEC network (MECN) is computation offloading in which computing nodes, with limited capabilities and performance, can offload computation-intensive tasks to other computing nodes in the network. Recently,...

This study addresses primal-dual dynamics for a stochastic programming problem for capacity network design. It is proven that consensus can be achieved on the \textit{here and now} variables which represent the capacity of the network. The main contribution is a heuristic approach which involves the formulation of the problem as a mean-field game....

This article presents a class of hierarchical mean-field-type games with multiple layers and non-quadratic polynomial costs. The decision-makers act in sequential order with informational differences. We first examine the single-layer case where each decision-maker does not have the information about the other control strategies. We derive the Nash...

In this paper, we study Berge equilibria in linear-quadratic mean-field-type game problems under a jump-diffusion-regime switching state dynamics that incorporate mean-field terms in both the states and cost functional. In the cost functional, we consider conditional variance of the states and control actions, conditional mean of states and control...

This article examines mean-field-type game problems by means of a direct method. We provide various solvable examples beyond the classical linear-quadratic game problems. These include quadratic-quadratic games and games with power, logarithmic, sine square, hyperbolic sine square payoffs. Non-linear state dynamics such as log-state, control-depend...

In this article, a class of mean-field-type games with discrete-continuous state spaces is considered. We establish Bellman systems which provide sufficiency conditions for mean-field-type equilibria in state-and-mean-field-type feedback form. We then derive unnormalized master adjoint systems (MASS). The methodology is shown to be flexible enough...

In this paper we study the problem of designing a collection of terminal payoff of mean-field type by interacting decision-makers to a specified terminal measure. We solve in a semi-explicit way a class of distributed planning in mean-field-type games with different objective functionals. We establish some relationships between the proposed framewo...

We present a novel distributed heterogeneous multi-population evolutionary dynamics approach, which can be used in diverse engineering applications as a distributed optimization-based algorithm. We also provide stability certificates of Nash equilibria under the proposed approach. Finally, over the end of this paper, an example illustrates the perf...

This article presents a class of Stackelberg mean-field-type games with multiple leaders and multiple followers. The decision-makers act in sequential order with informational differences. The state dynamics is driven by jump-diffusion processes and the cost function is non-quadratic and has a polynomial structure. The structures of Stackelberg str...

We present the design of a Gain-Scheduled Mean-Field-Type Control (GS-MFTC) for a non-linear Continuous Stirred Tank Reactor (CSTR). The MFTC controllers belong to a class of stochastic control techniques considering the distribution of the system states, and control inputs, while minimizing the variance of both variables of interest. The underlyin...

The coronavirus disease 2019 (COVID-19) pandemic is changing and impacting lives on a global scale. In this paper, we introduce a mean-field game model in controlling the propagation of epidemics on a spatial domain. The control variable, the spatial velocity, is first introduced for the classical disease models, such as the SIR model. For this pro...

Device-to-device (D2D) communications is a cell-free enabler of 5G and rising wireless communications demand between low-orbit satellite constellation, self-driving vehicles and unmanned aerial systems. Distributed computation (where channel state information is not available) schemes facilitate direct exchanges between mobile user equipment (UE) a...

In this article, we study mean-field-type games with jump-diffusion and regime switching in which the payoffs and the state dynamics depend not only on the state-action profile of the decision-makers but also on a measure of the state-action pair. The state dynamics is a measure-dependent process with jump-diffusion and regime switching. We derive...

Lecture 9

Lecture 8

In this paper we study linear-quadratic mean-field-type repeated games with arbitrary number of interacting decision-makers. Different information structures are examined: (i) perfect knowledge of the model, (ii) imperfect knowledge of the model; under perfect state observation. We provide semi-explicit solutions for both non-cooperative and cooper...

Lecture 7

Lecture 6: MFTG under Gauss-Volterra Processes

Recitation 5: Application of discrete time MFTG to microgrid energy storage

Lecture 5

Lecture 4

Recitation 4: Tokenized Blockchain-based Networks

In this article, a new class of mean-field-type games with both continuous state space are considered. We establish Bellman systems which provide sufficiency conditions for mean-field-type equilibria in state-and-mean-field-type feedback form. We then derive a class of master adjoint systems (MASS). The measure the state does not need to be normali...

In this article, a class of mean-field-type games e is considered. We establish Bellman systems which provide sufficiency conditions for mean-field-type equilibria in state-and-mean-field-type feedback form. We then derive master adjoint systems (MASS). The measure of the state does not need to be normalized and includes birth-and-death process. F...

Recitation 4.2 Blockchain-based Distributed Power Networks

Lecture 3

Recitation 3

Lecture 2

Recitation 2

recitation 1: Price formation games with incomplete information.

Lecture 0

Lecture 1

This article presents interaction problems with distribution-dependent quantities-of-interest in which a finite number of atomic decision-makers and multiple classes of non-atomic decision-makers are involved. We characterize mean-field-type Nash equilibria in state-and-mean-field-feedback strategies using a system of partial-integro differential e...

In this paper, we study and design a mean-field-type model predictive control, which is a class of risk-aware control considering within the cost functional not only the mean but also the variance of both the system states and control inputs. We formally present the relationship between the proposed approach and the chance-constrained control techn...

The problem of allocation in coalitional games with noisy observations and dynamic environments is considered. The evolution of the excess is modeled by a stochastic differential inclusion involving both deterministic and stochastic uncertainties. The main contribution is a set of linear matrix inequality conditions which guarantee that the distanc...

In this paper, we propose a co-opetitive mean-field- type game approach in which decision-makers interact with each other by partial cooperation and competition simultaneously. The proposed novel approach allows decision-makers’ preferences to evolve over time to cooperate with those who contribute to their utilities, and to compete with those who...

In this article, we study a linear-quadratic mean- field-type game problem under jump-diffusion-regime switching state dynamics that include mean-field terms in the states and in the cost function. In the cost functional, we consider conditional variance of both the states and control actions, mean of both states and control actions, and covariance...

we present MATLAB-based Mean-Field-Type Games (MFTG) Toolbox that allows simulation a diversity of scalar-valued and matrix-valued MFTG problems for an arbitrary number of players, e.g., non-cooperative, fully-cooperative and co-opetitive approaches. We present details of each of the developed tools together with several illustrative examples. In a...

n this paper, we present a user-friendly MatLab-based Mean-Field-Type Games (MFTG) Toolbox that allows simulating a diversity of scalar-valued and matrix-valued MFTG problems for an arbitrary number of players, e.g., non-cooperative, fully-cooperative and co-opetitive approaches. We present details of each one of the developed tools together with t...

Underwater communication remains a challenging technology via communication cables and the cost of underwater sensor network deployment is still very high. As an alternative, underwater wireless communication has been proposed and have received more attention in the last decade. Preliminary research indicated that Radio Frequency (RF) and Magneto-I...

This article examines the solvability of mean-field-type game problems by means of a direct method. We provide various solvable examples beyond the classical LQ game problems. It includes quadratic-quadratic games, power, logarithmic, sine square, hyperbolic sine square payoffs. Non-linear state dynamics such as control-dependent regime switching,...

Underwater sensor networks (UWSNs) are instructed for critical applications like military surveillance and underwater oil spills that conducted in a very massive three‐dimensional (3‐D) space that needs many underwater nodes (UNs) to cover the target area. Those UNs are not easy to recharge and cannot exploit solar power. MAC protocols deployed for...

. This paper studies blockchain cryptographic tokens by means of mean-field-type game theory. It introduces variance-aware utility function per decision-maker to capture the risk of cryptographic tokens associated with the uncertainties of technology adoption, network security, regulatory legislation and market volatility. We establish a relationsh...

This article examines mean-field-type games in which the state dynamics is driven by a Rosenblatt process. Rosenblatt processes are non-Markov and non-Gaussian. The cost functional is non-quadratic and includes a fractional-integral of an higher order polynomial. We identify semi-explicitly equilibrium strategies and equilibrium cost in linear stat...

This article presents a class of bi-level hierarchical mean-field-type games with several followers. The decision-makers act in sequential order with informational differences. The state dynamics is driven by jump-diffusion-regime switching and Gauss-Volterra processes which include fractional Brownian motion and multi-fractional Brownian motion. F...

In this paper we study linear-quadratic mean-field-type repeated games with arbitrary number of interacting decision-makers. Different information structures are examined: (i) perfect knowledge of the model, (ii) imperfect knowledge of the model; under perfect state observation. We provide semi-explicit solutions for both non-cooperative and cooper...

In this paper we study a class of matrix-valued linear-quadratic mean-field-type games for both the risk-neutral, risk-sensitive and robust cases. Non-cooperation, full cooperation and adversarial between teams are treated. We provide a semi-explicit solution for both problems by means of a direct method. The state dynamics is described by a matrix...

In this paper, we study a class of Constrained Linear-Quadratic Mean-Field-Type Games. The considered system dynamics are described including some mean-field terms, i.e., the expectation of both the system states and the control inputs. We obtain a semi-explicit solution for the problem by using the direct method in combination with some auxiliary...

A dynamics is forward-looking if one of its inputs involves future expectations of the system trajectory, using (possibly noisy) measurements on the past realizations. Forward-looking decision models find widespread use in social science, engineering, and computer science. The problem of forecasting forward-looking dynamics is of interest in game t...

This paper proposes a cooperative lane changing strategy using a transferable utility game's framework. This allows vehicles to engage in transactions where gaps in traffic are created in exchange for monetary compensation. Payoffs are calculated based on travel time differences and value of vehicle-travel-time (VOT). A cellular automaton is develo...

In this paper we examine mean-field-type games in blockchain-based distributed power networks with several different entities: investors, consumers, prosumers, producers and miners. Under a simple model of jump-diffusion and regime switching processes, we identify risk-aware mean-field-type optimal strategies for the decision-makers.

Quantised consensus has been used in the context of opinion dynamics. In this context agents interact with their neighbours and they change their opinion according to their interests and the opinions of their neighbours. We consider various quantised consensus models, where agents have different levels of susceptibility to the inputs received from...

Quantised consensus models for each case. (PDF)

Proof of Theorem 3. (PDF)