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Robert Mattmüller, Florian Geißer, Benedict Wright und Bernhard Nebel.
On the Relationship Between State-Dependent Action Costs and Conditional Effects in Planning.
In Proceedings of the 9th Workshop on Heuristics and Search for Domain-Independent Planning (HSDIP 2017). 2017.
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When planning for tasks that feature both state-dependent action costs and conditional effects using relaxation heuristics, the following problem appears: handling costs and effects separately leads to worse-than-necessary heuristic values, since we may get the more useful effect at the lower cost by choosing different values of a relaxed variable when determining relaxed costs and relaxed active effects.

In this paper, we show how this issue can be avoided by representing state-dependent costs and conditional effects uniformly, both as edge-valued multi-valued decision diagrams (EVMDDs) over different sets of edge values, and then working with their product diagram. We develop a theory of EVMDDs that is general enough to encompass state-dependent action costs, conditional effects, and even their combination.

We define relaxed effect semantics in the presence of state-dependent action costs and conditional effects, and describe how this semantics can be efficiently computed using product EVMDDs. This will form the foundation for informative relaxation heuristics in the setting with state-dependent costs and conditional effects combined.
Felix Lindner und Martin Mose Bentzen.
The HERA Approach to Morally Competent Robots.
In Proceedings of the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2017). 2017.
Barbara Kuhnert, Marco Ragni und Felix Lindner.
The Gap between Human's Attitute towards Robots in General and Human's Expectation of an Ideal Everyday Life Robot.
In Proceedings of the 2017 IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN 2017). 2017.
Felix Lindner, Laura Wächter und Martin Mose Bentzen.
Discussions About Lying with an Ethical Reasoning Robot.
In Proceedings of the 2017 IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN 2017). 2017.
Felix Lindner und Carola Eschenbach.
An Affordance-Based Conceptual Framework for Spatial Behavior of Social Robots.
In Raul Hakli und Johanna Seibt (Hrsg.), Sociality and Normativity for Robots --- Philosophical Inquiries into Human-Robot Interactions. Springer International Publishing 2017.
Barbara Kuhnert, Felix Lindner, Martin Mose Bentzen und Marco Ragni.
Perceived Difficulty of Moral Dilemmas Depends on Their Causal Structure: A Formal Model and Preliminary Results.
In Proceedings of the 39th Annual Meeting of the Cognitive Science Society CogSci 2017. 2017.
Thorsten Engesser, Thomas Bolander, Robert Mattmüller und Bernhard Nebel.
Cooperative Epistemic Multi-Agent Planning for Implicit Coordination.
In Proceedings of the Ninth Workshop on Methods for Modalities (M4M 2017). 2017.
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Epistemic planning can be used for decision making in multi-agent situations with distributed knowledge and capabilities. Recently, Dynamic Epistemic Logic (DEL) has been shown to provide a very natural and expressive framework for epistemic planning. We extend the DEL-based epistemic planning framework to include perspective shifts, allowing us to define new notions of sequential and conditional planning with implicit coordination. With these, it is possible to solve planning tasks with joint goals in a decentralized manner without the agents having to negotiate about and commit to a joint policy at plan time. First we define the central planning notions and sketch the implementation of a planning system built on those notions. Afterwards we provide some case studies in order to evaluate the planner empirically and to show that the concept is useful for multi-agent systems in practice.
Felix Lindner und Martin Mose Bentzen.
The Hybrid Ethical Reasoning Agent IMMANUEL.
In Proceedings of the 2017 Conference on Human-Robot Interaction (HRI2017), Late-Breaking Report. 2017.
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We introduce a novel software library that supports the implementation of hybrid ethical reasoning agents (HERA). The objective is to make moral principles available to robot programming. At its current stage, HERA can assess the moral permissibility of actions according to the principle of double effect, utilitarianism, and the do-no-harm principle. We present the prototype robot IMMANUEL based on HERA. The robot will be used to conduct research on joint moral reasoning in human-robot interaction.
Felix Lindner.
How To Count Multiple Personal-Space Intrusions in Social Robot Navigation.
In Proceedings of the Robo-Philosophy Conference 2016. 2016.
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One aspect of social robot navigation is to avoid personal space intrusions. Computationally, this can be achieved by introducing social costs into a robot's path planner's objective function. This article tackles the normative question of how robots should aggregate social costs incurred by multiple personal-space intrusions. Of particular interest is the question whether numbers should count, i.e., whether a robot ought to intrude into one person's personal space in order to aboid intruding into multiple personal spaces. This work proposes four different modes of aggregation of the costs of intrusions into personal space, discusses some of the philosophical arguments, and presents results from a pilot study.
Felix Lindner.
A Model of a Robot's Will Based on Higher-Order Desires.
In Proceedings of the IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN 2016). 2016.
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Autonomous robots implement decision making capacities on several layers of abstraction. Put in terms of desires, decision making evaluates desires to eventually commit to some most rational one. Drawing on the philosophical literature on volition and agency, this work introduces a conceptual model that enables robots to reason about which desires they want to want to realize, i.e., higher-order desires. As a result, six jointly exhaustive and pairwise disjoint types of choices are defined. Technical evaluation shows how to add a robot's will to its rational decision-making capacity. This guarantees that informed choices are possible even in cases rational decision making alone is indecisive. Further applications to modeling personality traits for human-robot interaction are discussed.
Dali Sun, Florian Geißer und Bernhard Nebel.
Towards Effective Localization in Dynamic Environments.
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2016). 2016.
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Localization in dynamic environments is still a challenging problem in robotics – especially if rapid and large changes occur irregularly. Inspired by SLAM algorithms, our Bayesian approach to this so-called dynamic localization problem divides it into a localization problem and a mapping problem, respectively. To tackle the localization problem we use a particle filter, coupled with a distance filter and a scan matching method, which achieves a more robust localization against dynamic obstacles. For the mapping problem we use an extended sensor model which results in an effective and precise map update effect. We compare our approach against other localization methods and evaluate the impact the map update effect has on the localization in dynamic environments.
Felix Lindner.
A Social Robot's Knowledge About Territories in Public Space.
In Proceedings of the 3rd Workshop on Public Space Human-Robot Interaction (PubRob 2016). 2016.
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Human territoriality is a microsocial phenomenon that displays the strong interrelations between action and space. Actions are spatially located, and because spaces that afford certain activities are rare, humans claim portions of space and restrict space access to particular agents. Thereby, they create territories. In public spaces, territories are usually short-term yet bravely defended: E.g., the table in a restaurant, the place in a queue at the checkout, the seat in the train. This abstract sketches a formal theory of territory. Its aim is to enable social robots to consider existing territories during decision making and planning both in order to avoid intrusions of others' territories and to claim territories for their own benefit.
Thomas Keller, Florian Pommerening, Jendrik Seipp, Florian Geißer und Robert Mattmüller.
State-dependent Cost Partitionings for Cartesian Abstractions in Classical Planning (Extended Abstract).
In Proceedings of the 39th German Conference on Artificial Intelligence (KI 2016). 2016.
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Abstraction heuristics are a popular method to guide optimal search algorithms in classical planning. Cost partitionings allow to sum heuristic estimates admissibly by partitioning action costs among the abstractions. We introduce state-dependent cost partitionings which take context information of actions into account, and show that an optimal state-dependent cost partitioning dominates its state-independent counterpart. We demonstrate the potential of state-dependent cost partitionings with a state-dependent variant of the recently proposed saturated cost partitioning, and show that it can sometimes improve not only over its state-independent counterpart, but even over the optimal state-independent cost partitioning.
Thomas Keller, Florian Pommerening, Jendrik Seipp, Florian Geißer und Robert Mattmüller.
State-dependent Cost Partitionings for Cartesian Abstractions in Classical Planning.
In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI 2016). 2016.
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Abstraction heuristics are a popular method to guide optimal search algorithms in classical planning. Cost partitionings allow to sum heuristic estimates admissibly by distributing action costs among the heuristics. We introduce state-dependent cost partitionings which take context information of actions into account, and show that an optimal state-dependent cost partitioning dominates its state-independent counterpart. We demonstrate the potential of our idea with a state-dependent variant of the recently proposed saturated cost partitioning, and show that it has the potential to improve not only over its state-independent counterpart, but even over the optimal state-independent cost partitioning. Our empirical results give evidence that ignoring the context of actions in the computation of a cost partitioning leads to a significant loss of information.
Yusra Alkhazraji und Martin Wehrle.
Sleep Sets Meet Duplicate Elimination.
In Proceedings of the Ninth Annual Symposium on Combinatorial Search (SoCS 2016) (SoCS 2016). 2016.
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The sleep sets technique is a path-dependent pruning method for state space search. In the past, the combination of sleep sets with graph search algorithms that perform duplicate elimination has often shown to be error-prone. In this paper, we provide the theoretical basis for the integration of sleep sets with common search algorithms in AI that perform duplicate elimination. Specifically, we investigate approaches to safely integrate sleep sets with optimal (best-first) search algorithms. Based on this theory, we provide an initial step towards integrating sleep sets within A* and additional state pruning techniques like strong stubborn sets. Our experiments show slight, yet consistent improvements on the number of generated search nodes across a large number of standard domains from the international planning competitions.
Tim Schulte und Bernhard Nebel.
Trial-based Heuristic Tree-search for Distributed Multi-Agent Planning.
In Proceedings of the Ninth Annual Symposium on Combinatorial Search (SoCS 2016) (SoCS 2016). 2016.
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We present a novel search scheme for privacy-preserving multi-agent planning, inspired by UCT search. We compare the presented approach to classical multi-agent forward search and evaluate it based on benchmarks from the CoDMAP competition.