no code implementations • 3 Apr 2024 • Till Hofmann, Hector Geffner
General policies represent reactive strategies for solving large families of planning problems like the infinite collection of solvable instances from a given domain.
no code implementations • 5 Feb 2024 • Till Hofmann, Stefan Schupp, Gerhard Lakemeyer
The most commonly used approach represents time by adding a real-valued fluent $\mathit{time}(a)$ that attaches a time point to each action and consequently to each situation.
no code implementations • 30 Dec 2023 • Till Hofmann
When reasoning about actions, e. g., by means of task planning or agent programming with Golog, the robot's actions are typically modeled on an abstract level, where complex actions such as picking up an object are treated as atomic primitives with deterministic effects and preconditions that only depend on the current state.
no code implementations • 26 Jul 2022 • Till Hofmann, Vaishak Belle
While this allows more precise robot models, the resulting programs are much harder to comprehend, because they need to deal with the noise, e. g., by looping until some desired state has been reached with certainty, and because the resulting action traces consist of a large number of actions cluttered with sensor noise.
no code implementations • 20 Jun 2022 • Daniel Swoboda, Till Hofmann, Tarik Viehmann, Gerhard Lakemeyer
One technique to tackle this problem is goal reasoning, where the agent not only reasons about its actions, but also about which goals to pursue.
no code implementations • 7 Apr 2022 • Till Hofmann, Stefan Schupp
While Golog is an expressive programming language to control the high-level behavior of a robot, it is often tedious to use on a real robotic system.
no code implementations • 7 Apr 2022 • Till Hofmann, Vaishak Belle
Abstraction is a commonly used process to represent some low-level system by a more coarse specification with the goal to omit unnecessary details while preserving important aspects.
no code implementations • 19 Feb 2021 • Till Hofmann, Gerhard Lakemeyer
We show that for programs over finite domains and with fully known initial state, the problem of synthesizing a controller that satisfies the constraints while preserving the effects of the original program can be reduced to MTL synthesis.
