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Nikolas Hohmann, Mariusz Bujny, Jürgen Adamy, Markus Olhofer , "Multi-objective 3D Path Planning for UAVs in Large-Scale Urban Scenarios", IEEE Congress on Evolutionary Computation, 2022.
AbstractIn the context of real-world path planning applications for Unmanned Aerial Vehicles (UAVs), aspects such as handling of multiple objectives (e.g., minimizing risk, path length, travel time, energy consumption, or noise pollution), generation of smooth trajectories in 3D space, and the ability to deal with urban environments have to be taken into account jointly by an optimization algorithm to provide practically feasible solutions. Since the cur...
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Rodrigo Canaan, Xianbo Gao, Julian Togelius, Andy Nealen, Stefan Menzel , "Generating and Adapting to Diverse Ad-Hoc Partners in Hanabi", IEEE Transactions on Games, 2022.
AbstractHanabi is a cooperative game that brings the problem of modeling other players to the forefront. In this game, coordinated groups of players can leverage pre-established conventions to great effect. In this paper, we focus on ad-hoc settings with no previous coordination between partners. We introduce a “Bayesian Meta-Agent” that maintains a belief distribution over hypotheses of partner policies. The policies that serve as initial hypotheses are...
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Thomas Schmitt, Matthias Hoffmann, Tobias Rodemann, Jürgen Adamy , "Incorporating Human Preferences in Decision Making for Dynamic Multi-Objective Optimization in Model Predictive Control", Inventions 2022, vol. 7, no. 3, 2022.
AbstractWe present a new two-step approach for automatized a posteriori decision making in multi-objective optimization problems. In the first step, a knee region is determined based on the normalized Euclidean distance from a hyperplane defined by the furthest Pareto solution and the negative unit vector. The size of the knee region depends on the Pareto front’s shape and a design parameter. In the second step, preferences for all objectives formula...
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Thomas Jatschka , "Computational Optimization Approaches for Distributing Service Points for Mobility Applications and Smart Charging of Electric Vehicles", Technical University Vienna, 2022.
AbstractFor many business models in the mobility domain an optimal distribution of service points in a customer community is needed. Examples are charging stations of electric vehicles (EVs), bicycle sharing stations, battery swapping stations, or repair stations. Two main challenges are to get the necessary data about the community and environment in order to estimate user demands, local constraints of potential locations, and other properties and to id...
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Leonore Röseler, Ingo Scholtes, Bernhard Sendhoff, Aniko Hannak , "Willing to revise? Confidence and Recommendation Adoption in AI-Assisted Image Recognition", International Conference on Hybrid Human-Artificial Intelligence (HHAI 2022), 2022.
AbstractArtificial intelligence (AI) is increasingly used to assist humans in various aspects of everyday life, including high-stakes decision-making. Nevertheless, the question how to design human-AI teams that optimally integrate the strengths of both parties, while mitigating their respective weaknesses, is still open. This work investigates how different mechanisms for the integration of AI-generated recommendations influence the performance of AI-as...
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Patricia Wollstadt and Matti Krüger , "Quantifying cooperation between artificial agents using information theory", HHAI2022: Augmenting Human Intellect, vol. 354, pp. 302 - 304, 2022.
AbstractWhen designing interactive human-machine systems, it is often assumed that it is desirable for such systems to behave cooperatively towards a human operator, to improve trust, acceptance, and usability, but also to increase task efficiency. To design cooperative HMI systems, we have to be able to define and quantitatively describe cooperative interactions, for example, to control, optimize, or evaluate system behavior. Despite the increased inter...
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Nazia Attari, David Schlangen, Heiko Wersing, Sina Zarriess , "Generating Coherent and Informative Descriptions for Groups of Visual Objects and Categories: A Simple Decoding Approach", INLG 2022 Proceedings, 2022.
AbstractState-of-the-art models in language and vision achieve very good performance on tasks concerned with captioning in stances of visual objects and reasoning about them, e.g. imposing distinctiveness of the instance-level description in the context of distractors. But these descriptions focus on isolated instances and cannot directly be used for describin g groups of instances and verbalizing knowledge on the level of categories. In this work, w...
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Stephen Friess , "Inductive Biases and Metaknowledge Representations for Search-based Optimization", University of Birmingham, 2022.
Abstract"What I do not understand, I can still create.", H. Sayama. The following work follows closely the aforementioned bonmot. Guided by questions such as: "How can evolutionary processes exhibit learning behavior and consolidate knowledge?", "What are cognitive models of problem-solving?" and "How can we harness these altogether as computational techniques?", we clarify within this work essentials required to implement them for metaheuristic search a...
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Xilu Wang , "Bayesian Evolutionary Optimization for Heterogeneously Expensive Multi-objective Optimization", University of Surrey, 2022.
AbstractVarious multi-objective optimization algorithms have been proposed with a common assumption that the evaluation of each objective function takes the same period of time. Little attention has been paid to more general and realistic optimization scenarios where different objectives are evaluated by different computer simulations or physical experiments with different time complexities (latencies) and only a very limited number of function evaluat...
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Hao Tong, Leandro L. Minku, Stefan Menzel, Bernhard Sendhoff, Xin Yao , "What Makes The Dynamic Capacitated Arc Routing Problem Hard To Solve: Insights From Fitness Landscape Analysis", The Genetic and Evolutionary Computation Conference, 2022.
AbstractThe Capacitated Arc Routing Problem (CARP) aims at assigning vehicles to serve tasks which are located at different arcs in a graph. However, the originally planned routes are easily affected by different dynamic events like newly added tasks. This gives rise to Dynamic CARP (DCARP) instances, which need to be efficiently optimized for new high-quality service plans in a short time. However, it is unknown which dynamic events make DCARP instances...
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