103,385 research outputs found
Time window temporal logic
This paper introduces time window temporal logic (TWTL), a rich expressive language for describing various time bounded specifications. In particular, the syntax and semantics of TWTL enable the compact representation of serial tasks, which are prevalent in various applications including robotics, sensor systems, and manufacturing systems. This paper also discusses the relaxation of TWTL formulae with respect to the deadlines of the tasks. Efficient automata-based frameworks are presented to solve synthesis, verification and learning problems. The key ingredient to the presented solution is an algorithm to translate a TWTL formula to an annotated finite state automaton that encodes all possible temporal relaxations of the given formula. Some case studies are presented to illustrate the expressivity of the logic and the proposed algorithms
Optimal Control of MDPs with Temporal Logic Constraints
In this paper, we focus on formal synthesis of control policies for finite
Markov decision processes with non-negative real-valued costs. We develop an
algorithm to automatically generate a policy that guarantees the satisfaction
of a correctness specification expressed as a formula of Linear Temporal Logic,
while at the same time minimizing the expected average cost between two
consecutive satisfactions of a desired property. The existing solutions to this
problem are sub-optimal. By leveraging ideas from automata-based model checking
and game theory, we provide an optimal solution. We demonstrate the approach on
an illustrative example.Comment: Technical report accompanying the CDC 2013 pape
Robust Control of Uncertain Markov Decision Processes with Temporal Logic Specifications
We present a method for designing robust controllers for dynamical systems with linear temporal logic specifications. We abstract the original system by a finite Markov Decision Process (MDP) that has transition probabilities in a specified uncertainty set. A robust control policy for the MDP is generated that maximizes the worst-case probability of satisfying the specification over all transition probabilities in the uncertainty set. To do this, we use a procedure from probabilistic model checking to combine the system model with an automaton representing the specification. This new MDP is then transformed into an equivalent form that satisfies assumptions for stochastic shortest path dynamic programming. A robust version of dynamic programming allows us to solve for a -suboptimal robust control policy with time complexity times that for the non-robust case. We then implement this control policy on the original dynamical system
Physics-based Motion Planning with Temporal Logic Specifications
One of the main foci of robotics is nowadays centered in providing a great
degree of autonomy to robots. A fundamental step in this direction is to give
them the ability to plan in discrete and continuous spaces to find the required
motions to complete a complex task. In this line, some recent approaches
describe tasks with Linear Temporal Logic (LTL) and reason on discrete actions
to guide sampling-based motion planning, with the aim of finding
dynamically-feasible motions that satisfy the temporal-logic task
specifications. The present paper proposes an LTL planning approach enhanced
with the use of ontologies to describe and reason about the task, on the one
hand, and that includes physics-based motion planning to allow the purposeful
manipulation of objects, on the other hand. The proposal has been implemented
and is illustrated with didactic examples with a mobile robot in simple
scenarios where some of the goals are occupied with objects that must be
removed in order to fulfill the task.Comment: The 20th World Congress of the International Federation of Automatic
Control, 9-14 July 201
Time Window Temporal Logic
This paper introduces time window temporal logic (TWTL), a rich expressivity
language for describing various time bounded specifications. In particular, the
syntax and semantics of TWTL enable the compact representation of serial tasks,
which are typically seen in robotics and control applications. This paper also
discusses the relaxation of TWTL formulae with respect to deadlines of tasks.
Efficient automata-based frameworks to solve synthesis, verification and
learning problems are also presented. The key ingredient to the presented
solution is an algorithm to translate a TWTL formula to an annotated finite
state automaton that encodes all possible temporal relaxations of the
specification. Case studies illustrating the expressivity of the logic and the
proposed algorithms are included
The decision problem of modal product logics with a diagonal, and faulty counter machines
In the propositional modal (and algebraic) treatment of two-variable
first-order logic equality is modelled by a `diagonal' constant, interpreted in
square products of universal frames as the identity (also known as the
`diagonal') relation. Here we study the decision problem of products of two
arbitrary modal logics equipped with such a diagonal. As the presence or
absence of equality in two-variable first-order logic does not influence the
complexity of its satisfiability problem, one might expect that adding a
diagonal to product logics in general is similarly harmless. We show that this
is far from being the case, and there can be quite a big jump in complexity,
even from decidable to the highly undecidable. Our undecidable logics can also
be viewed as new fragments of first- order logic where adding equality changes
a decidable fragment to undecidable. We prove our results by a novel
application of counter machine problems. While our formalism apparently cannot
force reliable counter machine computations directly, the presence of a unique
diagonal in the models makes it possible to encode both lossy and
insertion-error computations, for the same sequence of instructions. We show
that, given such a pair of faulty computations, it is then possible to
reconstruct a reliable run from them
Ambidexterity as practice : individual ambidexterity through paradoxical practices
Following the turn to practice in organization theory and the emerging interest in the microfoundations of ambidexterity, understanding the role of individuals in realizing ambidexterity approaches becomes crucial. Drawing insights from Greek philosophy on paradoxes, and practice theory on paradoxes and ambidexterity, we propose a view of individual ambidexterity grounded in paradoxical practices. Existing conceptualizations of ambidexterity are largely based on separation strategies. Contrary to this perspective, we argue that individual ambidexterity can be accomplished via paradoxical practices that renegotiate or transcend boundaries of exploration and exploitation. We identify three such paradoxical practices at the individual level that can advance understanding of ambidexterity: engaging in āhybrid tasks,ā capitalizing cumulatively on previous learning, and adopting a mindset of seeking synergies between the competing demands of exploration and exploitation
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