Zobrazeno 1 - 10
of 146
pro vyhledávání: '"Damoulas, Theodoros"'
In many real-world routing problems, decision makers must optimise over sparse graphs such as transportation networks with non-metric costs on the edges that do not obey the triangle inequality. Motivated by finding a sufficiently long running route
Externí odkaz:
http://arxiv.org/abs/2410.10440
Agent-based models (ABMs) are proliferating as decision-making tools across policy areas in transportation, economics, and epidemiology. In these models, a central object of interest is the discrete origin-destination matrix which captures spatial in
Externí odkaz:
http://arxiv.org/abs/2410.07352
Differential equations are important mechanistic models that are integral to many scientific and engineering applications. With the abundance of available data there has been a growing interest in data-driven physics-informed models. Gaussian process
Externí odkaz:
http://arxiv.org/abs/2409.13876
Decision making under uncertainty is challenging since the data-generating process (DGP) is often unknown. Bayesian inference proceeds by estimating the DGP through posterior beliefs about the model's parameters. However, minimising the expected risk
Externí odkaz:
http://arxiv.org/abs/2409.03492
Autor:
Zennaro, Fabio Massimo, Bishop, Nicholas, Dyer, Joel, Felekis, Yorgos, Calinescu, Anisoara, Wooldridge, Michael, Damoulas, Theodoros
Multi-armed bandits (MAB) and causal MABs (CMAB) are established frameworks for decision-making problems. The majority of prior work typically studies and solves individual MAB and CMAB in isolation for a given problem and associated data. However, d
Externí odkaz:
http://arxiv.org/abs/2404.17493
Autor:
Dyer, Joel, Bishop, Nicholas, Felekis, Yorgos, Zennaro, Fabio Massimo, Calinescu, Anisoara, Damoulas, Theodoros, Wooldridge, Michael
Agent-based simulators provide granular representations of complex intelligent systems by directly modelling the interactions of the system's constituent agents. Their high-fidelity nature enables hyper-local policy evaluation and testing of what-if
Externí odkaz:
http://arxiv.org/abs/2312.11158
Causal abstraction (CA) theory establishes formal criteria for relating multiple structural causal models (SCMs) at different levels of granularity by defining maps between them. These maps have significant relevance for real-world challenges such as
Externí odkaz:
http://arxiv.org/abs/2312.08107
Publikováno v:
Stat, vol. 13, no. 1, 2024, p. e656
A key challenge in agent-based mobility simulations is the synthesis of individual agent socioeconomic profiles. Such profiles include locations of agent activities, which dictate the quality of the simulated travel patterns. These locations are typi
Externí odkaz:
http://arxiv.org/abs/2307.02184
Measurement error occurs when a covariate influencing a response variable is corrupted by noise. This can lead to misleading inference outcomes, particularly in problems where accurately estimating the relationship between covariates and response var
Externí odkaz:
http://arxiv.org/abs/2306.01468
Structural causal models provide a formalism to express causal relations between variables of interest. Models and variables can represent a system at different levels of abstraction, whereby relations may be coarsened and refined according to the ne
Externí odkaz:
http://arxiv.org/abs/2305.04357