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Andreas Hertle und Bernhard Nebel.
Efficient Auction Based Coordination for Distributed Multi-Agent Planning in Temporal Domains Using Resource Abstraction.
In
Proceedings of the 41st German Conference on Artificial Intelligence (KI 2018).
2018.
(Abstract einblenden)
(Abstract ausblenden)
(PDF)
(BIB)
Recent advances in mobile robotics and AI promise to revolutionize industrial production.
As autonomous robots are able to solve more complex tasks, the difficulty of integrating various robot skills and coordinating groups of robots increases dramatically.
Domain independent planning promises a possible solution.
For single robot systems a number of successful demonstrations can be found in scientific literature.
However our experiences at the RoboCup Logistics League in 2017 highlighted a severe lack in plan quality when coordinating multiple robots.
In this work we demonstrate how out of the box temporal planning systems can be employed to increase plan quality for temporal multi-robot tasks.
An abstract plan is generated first and sub-tasks in the plan are auctioned off to robots, which in turn employ planning to solve these tasks and compute bids.
We evaluate our approach on two planning domains and find significant improvements in solution coverage and plan quality.
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Barbara Kuhnert, Felix Lindner, Martin Mose Bentzen und Marco Ragni.
Causal Structure of Moral Dilemmas Predicts Perceived Difficulty of Making a Decision.
In
Proceedings of the KogWis 2018 (Extended Abstract).
2018.
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Martin Mose Bentzen, Felix Lindner, Louise Dennis und Michael Fisher.
Moral Permissibility of Actions in Smart Home Systems.
In
Proceedings of the FLoC 2018 Workshop on Robots, Morality, and Trust through the Verification Lens (Extended Abstract).
2018.
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Hanna Stellmach und Felix Lindner.
Perception of an Uncertain Ethical Reasoning Robot: A Pilot Study.
In
Proceedings of Mensch und Computer 2018.
2018.
(Abstract einblenden)
(Abstract ausblenden)
The study investigates the effect of uncertainty expressed by a robot facing a moral dilemma.
Participants (N = 80) were shown a video of a robot explaining a moral dilemma and the
decision it makes. The robot either expressed certainty or uncertainty about its decision.
Participants rated how much blame the robot deserves for its action, the moral wrongness
of the action, and their impression of the robot in terms of four scale dimensions measuring
social perception. The results suggest that participants that were not familiar with the moral
dilemma assign more blame to the robot for the same action when it expresses uncertainty,
while expressed uncertainty has less effect on moral wrongness judgments. There was no
significant effect of expressed uncertainty on participants’ impression of the robot. We discuss
implications of this result for the design of social robots.
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David Speck, Florian Geißer und Robert Mattmüller.
Symbolic Planning with Edge-Valued Multi-Valued Decision Diagrams.
In
Proceedings of the 28th International Conference on Automated Planning and Scheduling (ICAPS 2018).
2018.
(Abstract einblenden)
(Abstract ausblenden)
(PDF)
(technical report with proofs; PDF)
Symbolic representations have attracted significant attention in optimal
planning. Binary Decision Diagrams (BDDs) form the basis for symbolic search
algorithms. Closely related are Algebraic Decision Diagrams (ADDs), used to
represent heuristic functions.
Also, progress was made in dealing with models that take state-dependent
action costs into account. Here, costs are represented as Edge-valued
Multi-valued Decision Diagrams (EVMDDs), which can be exponentially more
compact than the corresponding ADD representation. However, they were not
yet considered for symbolic planning.
In this work, we study EVMDD-based symbolic search for optimal planning. We
define EVMDD-based representations of state sets and transition relations,
and show how to compute the necessary operations required for EVMDD-A*. This
EVMDD-based version of symbolic A* generalizes its BDD variant, and allows
to solve planning tasks with state-dependent action costs.
We prove theoretically that our approach is sound, complete and optimal.
Additionally, we present an empirical analysis comparing EVMDD-A* to BDD-A*
and explicit A* search. Our results underscore the usefulness of symbolic
approaches and the feasibility of dealing with models that go beyond unit
costs.
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Felix Lindner und Martin Mose Bentzen.
A Formalization of Kant's Second Formulation of the Categorical Imperative.
In
Proceedings of the 14th International Conference on Deontic Logic and Normative Systems (DEON).
2018.
(Abstract einblenden)
(Abstract ausblenden)
We present a formalization and computational implementation of the second formulation of Kant's categorical imperative. This ethical principle requires an agent to never treat someone merely as a means but always also as an end. Here we interpret this principle in terms of how persons are causally affected by actions. We introduce Kantian causal agency models in which moral patients, actions, goals, and causal influence are represented, and we show how to formalize several readings of Kant's categorical imperative that correspond to Kant's concept of strict and wide duties towards oneself and others. Stricter versions handle cases where an action directly causally affects oneself or others, whereas the wide version maximizes the number of persons being treated as an end. We discuss limitations of our formalization by pointing to one of Kant's cases that the machinery cannot handle in a satisfying way.
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Felix Lindner, Robert Mattmüller und Bernhard Nebel.
Moral Permissibility of Action Plans.
In
Proceedings of the ICAPS Workshop on EXplainable AI Planning (XAIP).
2018.
(Abstract einblenden)
(Abstract ausblenden)
Research in classical planning so far was mainly concerned with generating a satisficing or an optimal plan.
However, if such systems are used to make decisions that are relevant to humans, one should also consider
the ethical consequences that generated plans can have. We address this challenge by analyzing in how
far it is possible to generalize existing approaches of machine ethics to automatic planning systems.
Traditionally, ethical principles are formulated in an action-based manner, allowing to judge the execution of
one action. We show how such a judgment can be generalized to plans.
Further, we study the complexity of making ethical judgment about plans.
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Benedict Wright, Oliver Brunner und Bernhard Nebel.
On the Importance of a Research Data Archive.
In
Proceedings of the eighth Symposium on Educational Advances in Artificial Intelligence (EAAI 2018).
2018.
(Abstract einblenden)
(Abstract ausblenden)
(PDF)
As research becomes more and more data intensive, managing this data becomes a major challenge in any organization. At university level there is seldom a unified data management system in place. The general approach to storing data in such environments is to deploy network storage. Each member can store their data organized to their own likings in their dedicated location on the network. Additionally, users tend to store data in distributed manner such as on private devices, portable storage, or public and private repositories. Adding to this complexity, it is common for university departments to have high fluctuation of staff, resulting in major loss of information and data on an employee's departure. A common scenario then is that it is known that certain data has already been created via experiments or simulation. However, it can not be retrieved, resulting in a repetition of generation, which is costly and time-consuming. Additionally, as of recent years, publishers and funding agencies insist on storing, sharing, and reusing existing research data. We show how digital preservation can help group leaders and their employees cope with these issues, by introducing our own archival system OntoRAIS.
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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 Thirty-Second AAAI Conference on Artificial Intelligence (AAAI 2018).
2018.
(Abstract einblenden)
(Abstract ausblenden)
(PDF)
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.
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Glenda Hannibal und Felix Lindner.
Transdisciplinary Reflections on Social Robotics in Academia and Beyond.
In
Proceedings of Robo-Philosophy 2018.
2018.
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Johannes Aldinger und Bernhard Nebel.
Interval Based Relaxation Heuristics for Numeric Planning
with Action Costs.
In
KI 2017:Advances in Artificial Intelligence (KI 2017), S. 15-28.
Springer International Publishing 2017.
(Abstract einblenden)
(Abstract ausblenden)
(PDF)
Many real-world problems can be expressed in terms of states and
actions that modify the world to reach a certain goal. Such
problems can be solved by automated planning. Numeric planning
supports numeric quantities such as resources or physical
properties in addition to the propositional variables from
classical planning. We approach numeric planning with heuristic
search and introduce adaptations of the relaxation heuristics
hmax, hadd and hFF to interval
based relaxation frameworks. In contrast to previous approaches,
the heuristics presented in this paper are not limited to
fragments of numeric planning with instantaneous actions (such as
linear or acyclic numeric planning tasks) and support action
costs.
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Benedict Wright und Robert Mattmüller.
Automated Data Management Workflow Generation with Ontologies and Planning.
In
Proceedings of the 30th Workshop on Planen/Scheduling und Konfigurieren/Entwerfen (PUK 2016).
2016.
(PDF)
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Andreas Hertle und Bernhard Nebel.
Identifying Good Poses When Doing Your Household Chores: Creation and Exploitation of Inverse Surface Reachability Maps.
In
Proceedings of the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2017).
2017.
(Abstract einblenden)
(Abstract ausblenden)
(PDF)
In current approaches to combined task and motion planning, usually symbolic planning and sampling based motion-planning are integrated. One problem is here to come up with good samples. We address the problem of identifying useful poses for a robot close to working surfaces such as tables or shelves. Our approach is based on reachability inversion which answers the question: where should the robot be located in order to reach a certain object? We extend the concept from point-based objects to flat polygonal surfaces in order to enable the robot to have a a good grasping position for many objects. Our approach allows to quickly sample multiple distinct poses for the robot from an prior computed distribution. Further we show how sampling from an inverse reachability distribution can be integrated into a CTAMP system.
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F. Burget, L.D.J. Fiederer, D.Kuhner, M.Völker, Johannes Aldinger, R.T. Schirrmeister, C.Do, J.Boedecker, Bernhard Nebel, T.Ball und W.Burgard.
Acting Thoughts: Towards a Mobile Robotic Service Assistant for Users with Limited Communication Skills.
In
Proceedings of the European Conference on Mobile Robotics (ECMR 2017), S. 385-390.
2017.
(Abstract einblenden)
(Abstract ausblenden)
(PDF)
As autonomous service robots become more affordable and thus
available also for the general public, there is a growing need
for user friendly interfaces to control the robotic
system. Currently available control modalities typically expect
users to be able to express their desire through either touch,
speech or gesture commands. While this requirement is fulfilled
for the majority of users, paralyzed users may not be able to
use such systems. In this paper, we present a novel framework,
that allows these users to interact with a robotic service
assistant in a closed-loop fashion, using only thoughts. The
brain-computer interface (BCI) system is composed of several
interacting components, i.e., non-invasive neuronal signal
recording and decoding, high-level task planning, motion and
manipulation planning as well as environment perception. In
various experiments, we demonstrate its applicability and
robustness in real world scenarios, considering fetch-and-carry
tasks and tasks involving human-robot interaction. As our
results demonstrate, our system is capable of adapting to
frequent changes in the environment and reliably completing
given tasks within a reasonable amount of time. Combined with
high-level planning and autonomous robotic systems, interesting
new perspectives open up for non-invasive BCI-based human-robot
interactions.
