Reasoning about goal-directed real-time teleo-reactive programs

The teleo-reactive programming model is a high-level approach to developing real-time systems that supports hierarchical composition and durative actions. The model is different from frameworks such as action systems, timed automata and TLA+, and allows programs to be more compact and descriptive of their intended behaviour. Teleo-reactive programs are particularly useful for implementing controllers for autonomous agents that must react robustly to their dynamically changing environments. In this paper, we develop a real-time logic that is based on Duration Calculus and use this logic to formalise the semantics of teleo-reactive programs. We develop rely/guarantee rules that facilitate reasoning about a program and its environment in a compositional manner. We present several theorems for simplifying proofs of teleo-reactive programs and present a partially mechanised method for proving progress properties of goal-directed agents. © 2013 British Computer Society

The logic of unwitting collective agency

The paper is about the logic of expressions of the form `agent x brings it about that A is the case', or `agent x is responsible for its being the case that A', or `the actions of agent x are the cause of its being the case that A'. Agents could be deliberative (human or computer) agents, purely reactive agents, or simple computational devices. The `brings it about' modalities are intended to express unintentional, perhaps even accidental, consequences of an agent's actions, as well as possibly intentional (intended) ones. Since we make no assumptions at all about the reasoning or perceptual capabilities of the agents we refer to this form of agency as `unwitting'; unwitting can mean both inadvertent and unaware. The semantical framework is a form of labelled transition system extended with an extra component that picks out the actions of a particular agent in a transition, or its `strand' as we call it. We de ne a modal language for talking about the actions of individual agents or groups of agents in transitions, including two de ned modalities of the (unwitting) `brings it about' kind. The novel feature is the switch of attention from talking about an agent's bringing it about that a certain state of a airs exists to talking about an agent's bringing it about that a transition has a certain property. The middle part of the paper presents axiomatisations of the logic, and comments on relationships to other work, in particular on resemblances to P orn's (1977) logic of `brings it about'. The last part is concerned with characterisations of (unwitting) collective agency, that is, the logic of expressions of the form `the set G of agents, collectively though perhaps unwittingly, brings it about that A'

Building an environment model using depth information

Modeling the environment is one of the most crucial issues for the development and research of autonomous robot and tele-perception. Though the physical robot operates (navigates and performs various tasks) in the real world, any type of reasoning, such as situation assessment, planning or reasoning about action, is performed based on information in its internal world. Hence, the robot's intentional actions are inherently constrained by the models it has. These models may serve as interfaces between sensing modules and reasoning modules, or in the case of telerobots serve as interface between the human operator and the distant robot. A robot operating in a known restricted environment may have a priori knowledge of its whole possible work domain, which will be assimilated in its World Model. As the information in the World Model is relatively fixed, an Environment Model must be introduced to cope with the changes in the environment and to allow exploring entirely new domains. Introduced here is an algorithm that uses dense range data collected at various positions in the environment to refine and update or generate a 3-D volumetric model of an environment. The model, which is intended for autonomous robot navigation and tele-perception, consists of cubic voxels with the possible attributes: Void, Full, and Unknown. Experimental results from simulations of range data in synthetic environments are given. The quality of the results show great promise for dealing with noisy input data. The performance measures for the algorithm are defined, and quantitative results for noisy data and positional uncertainty are presented

Intention as Commitment toward Time

In this paper we address the interplay among intention, time, and belief in dynamic environments. The first contribution is a logic for reasoning about intention, time and belief, in which assumptions of intentions are represented by preconditions of intended actions. Intentions and beliefs are coherent as long as these assumptions are not violated, i.e. as long as intended actions can be performed such that their preconditions hold as well. The second contribution is the formalization of what-if scenarios: what happens with intentions and beliefs if a new (possibly conflicting) intention is adopted, or a new fact is learned? An agent is committed to its intended actions as long as its belief-intention database is coherent. We conceptualize intention as commitment toward time and we develop AGM-based postulates for the iterated revision of belief-intention databases, and we prove a Katsuno-Mendelzon-style representation theorem.Comment: 83 pages, 4 figures, Artificial Intelligence journal pre-prin

A model for trustworthy orchestration in the internet of things

Embedded systems such as Cyber-Physical Systems (CPS) are typically designed as a network of multiple interacting elements with physical input (or sensors) and output (or actuators). One aspect of interest of open systems is fidelity, or the compliance between physical figures of interest and their internal representation. High fidelity is defined as a stable mapping between actions in the physical domain and intended or expected values in the system domain and deviations from fidelity are quantifiable over time by some appropriate informative variable. In this paper, we provide a model for designing such systems based on a framework for trustworthiness monitoring and we provide a Jason implementation to evaluate the feasibility of our approach. In particular, we build a bridge between a standard publish/subscribe framework for CPS called MQTT and Jason to enable automatic reasoning about trustworthines

A model for trustworthy orchestration in the internet of things

Embedded systems such as Cyber-Physical Systems (CPS) are typically designed as a network of multiple interacting elements with physical input (or sensors) and output (or actuators). One aspect of interest of open systems is fidelity, or the compliance between physical figures of interest and their internal representation. High fidelity is defined as a stable mapping between actions in the physical domain and intended or expected values in the system domain and deviations from fidelity are quantifiable over time by some appropriate informative variable. In this paper, we provide a model for designing such systems based on a framework for trustworthiness monitoring and we provide a Jason implementation to evaluate the feasibility of our approach. In particular, we build a bridge between a standard publish/subscribe framework for CPS called MQTT and Jason to enable automatic reasoning about trustworthines

Towards an Indexical Model of Situated Language Comprehension for Cognitive Agents in Physical Worlds

We propose a computational model of situated language comprehension based on the Indexical Hypothesis that generates meaning representations by translating amodal linguistic symbols to modal representations of beliefs, knowledge, and experience external to the linguistic system. This Indexical Model incorporates multiple information sources, including perceptions, domain knowledge, and short-term and long-term experiences during comprehension. We show that exploiting diverse information sources can alleviate ambiguities that arise from contextual use of underspecific referring expressions and unexpressed argument alternations of verbs. The model is being used to support linguistic interactions in Rosie, an agent implemented in Soar that learns from instruction.Comment: Advances in Cognitive Systems 3 (2014

Features and Fluents for Logic Programming: Non-simulative Algebraic Semantics

A Non-simulative Algebraic Semantics is defined and its range of applicability is proven to be the K-RACi class of the Features and Fluents framework. The comparative assessment reveals the semantics epistemologically equivalent and ontologically stronger than the Abductive Logic Programming, the Action Description Language A and the PMON entailment. The semantics is shown to be decidable