Automated Controller Synthesis for Timeline-based Games

Core Concepts

This paper presents an effective and computationally optimal approach to synthesize controllers for timeline-based games, which can handle both temporal uncertainty and general nondeterminism in a uniform way.

Abstract

The paper introduces the concept of timeline-based games, which extends the timeline-based planning paradigm to handle general nondeterminism. It has been shown that determining the existence of a winning strategy for such games is 2EXPTIME-complete. However, a concrete approach to synthesize controllers implementing such strategies was missing. The key contributions of this work are: It provides a detailed account of the general timeline-based planning and game framework. It develops an effective and computationally optimal approach to directly construct a deterministic finite-state automaton that recognizes solution plans for a given timeline-based game. It shows how to turn such an automaton into the arena of a reachability game, for which many controller synthesis techniques are available. The proposed method addresses the limitations of previous techniques by avoiding the construction of large and complex intermediate structures, and directly building a deterministic automaton of an optimal doubly-exponential size.

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Key Insights Distilled From

Controller Synthesis for Timeline-based Games

by Renato Acamp... at arxiv.org 04-10-2024

https://arxiv.org/pdf/2307.12289.pdf

Deeper Inquiries

What are some potential real-world applications of timeline-based games and the proposed controller synthesis approach

The potential real-world applications of timeline-based games and the proposed controller synthesis approach are diverse and impactful. One application could be in autonomous systems, such as self-driving cars or drones, where planning and executing actions based on temporal constraints are crucial. By synthesizing controllers for timeline-based games, these systems can make decisions in real-time, considering both temporal uncertainty and general nondeterminism. This can lead to more efficient and reliable autonomous operations. Another application could be in manufacturing processes where scheduling and coordination of tasks are time-sensitive. By using timeline-based games and controller synthesis, manufacturers can optimize production schedules, manage resources effectively, and adapt to changing conditions dynamically. This can improve productivity, reduce downtime, and enhance overall operational efficiency. Furthermore, in healthcare settings, especially in emergency response systems or patient care management, timeline-based games can help in planning and executing critical actions within specified timeframes. By synthesizing controllers based on temporal constraints, healthcare providers can ensure timely interventions, streamline workflows, and improve patient outcomes.

How can the proposed technique be extended to handle more expressive temporal constraints or richer game settings beyond reachability objectives

The proposed technique can be extended to handle more expressive temporal constraints or richer game settings beyond reachability objectives by incorporating advanced formalisms and algorithms. One way to enhance the approach is to integrate more complex temporal logics, such as Linear Temporal Logic (LTL) or Computation Tree Logic (CTL), to capture intricate temporal relationships and constraints. This would allow for a more nuanced representation of system behaviors and requirements. Additionally, the technique can be extended to consider multi-objective optimization, where the controller synthesis aims to satisfy multiple objectives simultaneously, such as minimizing costs, maximizing efficiency, and ensuring safety. By incorporating multi-objective optimization techniques, the approach can provide more robust and versatile solutions for complex systems with diverse objectives. Moreover, the technique can be adapted to handle stochastic temporal constraints, where the timing of events is probabilistic rather than deterministic. By incorporating probabilistic models and algorithms, the approach can address scenarios with uncertain temporal dynamics, providing more adaptive and resilient controller synthesis solutions.

What are the implications of the 2EXPTIME-completeness result for the practical feasibility of timeline-based game solving, and how can the proposed approach help address the inherent complexity challenges

The 2EXPTIME-completeness result for timeline-based game solving indicates that the problem is highly complex and computationally challenging. This complexity poses significant obstacles to practical feasibility, especially in real-time applications or systems with stringent performance requirements. However, the proposed approach can help address these challenges by providing an effective and computationally optimal method for synthesizing controllers. By leveraging deterministic automata and efficient algorithms for controller synthesis, the proposed approach can streamline the process of finding winning strategies in timeline-based games. This can significantly reduce the computational burden and make the controller synthesis more practical and scalable for real-world applications. Furthermore, the proposed approach's optimization techniques and structured methodology can help mitigate the inherent complexity of timeline-based game solving. By providing a systematic and efficient way to handle temporal constraints and nondeterminism, the approach can improve the overall feasibility and applicability of timeline-based games in various domains.