Jean-François Alexis Baffier

Internet Initiative Japan · Research Lab

Quantum Annealing is an optimization process taking advantage of quantum tunneling to search for the global optimum of an optimization problem, although, being a heuristic method, there is no guarantee to find the global optimum. Optimization problems solved by a Quantum Annealer machine are modeled as Quadratic Unconstrained Binary Optimization (q...

In Constraint Programming, constraints are usually represented as predicates allowing or forbidding combinations of values. However, some algorithms can exploit a finer representation: error functions. By associating a function to each constraint type to evaluate the quality of an assignment, it extends the expressiveness of regular Constraint Sati...

Cost Function Networks (CFN) are a formalism in Constraint Programming to model combinatorial satisfaction or optimization problems. By associating a function to each constraint type to evaluate the quality of an assignment, it extends the expressivity of regular CSP/COP formalisms but at a price of making harder the problem modeling. Indeed, in ad...

Graphs are commonly used in mathematics to represent some relationships between items. However, as simple objects, they sometimes fail to capture all relevant aspects of real-world data. To address this problem, we generalize them and model interactions over time with multilayer structure. We build and test several centralities to assess the import...

Graphs are commonly used in mathematics to represent some relationships between items. However, as simple objects, they sometimes fail to capture all relevant aspects of real-world data. To address this problem, we generalize them and model interactions over time with multilayer structure. We build and test several centralities to assess the import...

We introduce the family of $k$-gap-planar graphs for $k \geq 0$, i.e., graphs that have a drawing in which each crossing is assigned to one of the two involved edges and each edge is assigned at most $k$ of its crossings. This definition finds motivation in edge casing, as a $k$-gap-planar graph can be drawn crossing-free after introducing at most...

We propose to solve the adaptive network flow problem via a bilevel optimization framework. In this problem, we aim to find a flow that is most robust against any k edges attack. There is an exact algorithm proposed to solve the problem in a specific class of input graphs. However, for some input graphs that are not in that class, a flow obtained f...

Knowledge is created and transmitted through generation. Innovation is often seen as a generative process from collective intelligence, but how does innovation emerges from the blending of accumulated knowledge, and from which path an innovation mostly inherit? A citation network can be seen as a perfect example of a generative process leading to i...

[This corrects the article DOI: 10.1007/s41109-017-0035-2.].

We introduce the family of $k$-gap-planar graphs for $k \geq 0$, i.e., graphs that have a drawing in which each crossing is assigned to one of the two involved edges and each edge is assigned at most $k$ of its crossings. This definition is motivated by applications in edge casing, as a $k$-gap-planar graph can be drawn crossing-free after introduc...

Knowledge is created and transmitted through generations, and innovation is often seen as a process generated from collective intelligence. There is rising interest in studying how innovation emerges from the blending of accumulated knowledge, and from which path an innovation mostly inherits. A citation network can be seen as a perfect example of...

The {\em compressed stack} is a data structure designed by Barba {\em et al.} (Algorithmica 2015) that allows to reduce the amount of memory needed by an algorithm (at the cost of increasing its runtime). In this paper we introduce the first implementation of this data structure and make its source code publicly available. Together with the impleme...

In this paper we study a cooperative card game called Hanabi from the viewpoint of algorithmic combinatorial game theory. In Hanabi, each card has one among c colors and a number between 1 and n. The aim is to make, for each color, a pile of cards of that color with all increasing numbers from 1 to n. At each time during the game, each player holds...

This paper presents GHOST, a combinatorial optimization framework that a real-Time strategy (RTS) AI developer can use to model and solve any problem encoded as a constraint satisfaction/optimization problem (CSP/COP). We show a way to model three different problems as a CSP/COP, using instances from the RTS game StarCraft as test beds. Each proble...

We investigate variants of the max-flow problem in a network under attacks. The network interdiction problem is to find the minimum max-flow value among networks that can be obtained by deleting each set of links. The adaptive network flow problem is to find a flow of the network such that the flow value is maximum against any set of links attack,...

This paper studies a cooperative card game called Hanabi from an algorithmic combinatorial game theory viewpoint. The aim of the game is to play cards from $1$ to $n$ in increasing order (this has to be done independently in $c$ different colors). Cards are drawn from a deck one by one. Drawn cards are either immediately played, discarded or stored...

The Skull and Roses (also known simply as Skull) is a multiplayer card game with small stochasticity, imperfect information, and partially observable outcomes. Consequently, like in the case of poker, it requires to mix bluffs, opponent modeling, and coalitions as high-level strategic plays, achieving all this with a very simple set of rules and el...

This work improves algorithms for finding network flows both sustainable and robust against multilink-attack (MLA). It brings out the relationship between sustainability (flow solution before attack known as MLA-reliable flow) and robustness (flow value after attack known as MLA-robust flow). Both problems are known to be NP-hard. However, exact po...

This paper presents GHOST, a combinatorial optimization solver an RTS AI developer can use as a blackbox to solve any problems encoded by a constraint satisfaction/optimization problem. We show a way to model three very different RTS problems by a constraint satisfaction/optimization problem, each problem belonging to a specific level of abstractio...

In this paper, we propose an algorithm that outperforms an algorithm used for maximizing barrier coverage in battery harvesting sensor network proposed by DeWitt, Patt, and Shi. The previous work aims to maximize the robustness of the information transmission between two sensor nodes, while guarantee that the amount of energy harvested by each node...

In this work, we investigate properties of the function taking the real value $h$ to the max $h$-route flow value, and apply the result to solve robust network flow problems. We show that the function is piecewise hyperbolic, and modify a parametric optimization technique, the ES algorithm, to find this function. The running time of the algorithm i...

We consider two variants of a max-flow problem against k edge failures, each of which can be both approximated by a multiroute flow algorithm. The maximum k-robust flow problem is to find the minimum max-flow value among \({m\choose k}\) networks that can be obtained by deleting each set of k edges. The maximum k-balanced flow problem is to find a...

In this paper, we analyze the game with large number of short states named Skull & Roses from a computer science point of view. We describe the game in a formal way, and use that formulation to obtain boundaries and average value on the game length, state-space size, and the game tree size. As a result, we can imply that developing an AI strategy f...