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Alexander Aurell

Alexander Aurell
Silo AI · Stockholm

Doctor of Engineering
AI Scientist at Silo AI

About

13
Publications
664
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83
Citations

Publications

Publications (13)
Article
Full-text available
In this paper, we analyze linear-quadratic stochastic differential games with a continuum of players interacting through graphon aggregates, each state being subject to idiosyncratic Brownian shocks. The major technical issue is the joint measurability of the player state trajectories with respect to samples and player labels, which is required to...
Article
Full-text available
We consider a game for a continuum of non-identical players evolving on a finite state space. Their heterogeneous interactions are represented with a graphon, which can be viewed as the limit of a dense random graph. A player’s transition rates between the states depend on their control and the strength of interaction with the other players. We dev...
Preprint
We consider a game for a continuum of non-identical players evolving on a finite state space. Their heterogeneous interactions are represented by a graphon, which can be viewed as the limit of a dense random graph. The player's transition rates between the states depend on their own control and the interaction strengths with the other players. We d...
Preprint
In this paper, we analyze linear-quadratic stochastic differential games with a continuum of players interacting through graphon aggregates, each state being subject to idiosyncratic Brownian shocks. The major technical issue is the joint measurability of the player state trajectories with respect to samples and player labels, which is required to...
Preprint
Motivated by models of epidemic control in large populations, we consider a Stackelberg mean field game model between a principal and a mean field of agents evolving on a finite state space. The agents play a non-cooperative game in which they can control their transition rates between states to minimize an individual cost. The principal can influe...
Preprint
Full-text available
It is common to model learning in games so that either a deterministic process or a finite state Markov chain describes the evolution of play. Such processes can however produce undesired outputs, where the players' behavior is heavily influenced by the modeling. In simulations we see how the assumptions in (Young, 1993), a well-studied model for s...
Preprint
This paper introduces a system of stochastic differential equations (SDE) of mean-field type that by means of sticky boundaries and boundary diffusion accounts for the possibility of pedestrians to spend time at, and to move along, walls. As an alternative to Neumann-type boundary conditions, sticky boundaries and boundary diffusion have a 'smoothi...
Article
Full-text available
In this paper, mean-field type games between two players with backward stochastic dynamics are defined and studied. They make up a class of non-zero-sum, non-cooperating, differential games where the players’ state dynamics solve backward stochastic differential equations (BSDE) that depend on the marginal distributions of player states. Players tr...
Preprint
In this paper, mean-field type games between two players with backward stochastic dynamics are defined and studied. They make up a class of non-zero-sum differential games where the players' state dynamics solve backward stochastic differential equations (BSDEs) that depend on the marginal distributions of player states. Players try to minimize the...
Article
This paper suggests a mean-field model for the movement of tagged pedestrians, distinguishable from a surrounding crowd, with a targeted final destination. The tagged pedestrians move through a dynamic crowd, interacting with it while optimizing their path. The model includes distribution-dependent effects like congestion and crowd aversion. The be...
Article
We extend the class of pedestrian crowd models introduced by Lachapelle and Wolfram [Transp. Res. B: Methodol., 45 (2011), pp. 1572–1589] to allow for nonlocal crowd aversion and arbitrarily but finitely many interacting crowds. The new crowd aversion feature grants pedestrians a “personal space” where crowding is undesirable. We derive the model f...

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