We propose a timed and soft extension of Concurrent Constraint Programming. The time extension is based on the hypothesis of bounded asynchrony: the computation takes a bounded period of time and is measured by a discrete global clock. Action prefixing is then considered as the syntactic marker which distinguishes a time instant from the next one. Supported by soft constraints instead of crisp ones, tell and ask agents are now equipped with a preference (or consistency) threshold which is used to determine their success or suspension. In the paper we provide a language to describe the agents behavior, together with its operational and denotational semantics, for which we also prove the compositionality and correctness properties. After presenting a semantics using maximal parallelism of actions, we also describe a version for their interleaving on a single processor (with maximal parallelism for time elapsing). Coordinating agents that need to take decisions both on preference values and time events may benefit from this language. To appear in Theory and Practice of Logic Programming (TPLP).
A second difference relies in the transfer of information across time boundaries. In @cite_12 and @cite_27 , the programmer has to explicitly transfer the (positive) information from a time instant to the next one, by using special primitives that allow one to control the temporal evolution of the system. In fact, at the end of a time interval all the constraints accumulated and all the processes suspended are discarded, unless they are arguments to a specific primitive. On the contrary, no explicit transfer is needed in tsccp , since the computational model is based on the monotonic evolution of the store which is usual in ccp .
@cite_27 @cite_12
1994157580 2130182605 2109187338 2070085078
Abstract Synchronous programming (Berry, 1989) is a powerful approach to programming reactive systems. Following the idea that “processes are relations extended over time” (Abramsky, 1993), we propose a simple but powerful model for timed, determinate computation, extending the closure-operator model for untimed concurrent constraint programming (CCP). In . (1994a) we had proposed a model for this called tcc—here we extend the model of tcc to express strong time-outs: if an event A does not happen through time t , cause event B to happen at time t . Such constructs arise naturally in practice (e.g. in modeling transistors) and are supported in synchronous programming languages. The fundamental conceptual difficulty posed by these operations is that they are non-monotonic. We provide compositional semantics to the non-monotonic version of concurrent constraint programming (Default cc) obtained by changing the underlying logic from intuitionistic logic to Reiter's default logic. This allows us to use the same construction (uniform extension through time) to develop Default cc as we had used to develop tcc from cc. Indeed the smooth embedding of cc processes into Default cc processes lifts to a smooth embedding of tcc processes into Default cc processes. We identify a basic set of combinators (that constitute the Default cc programming framework), and provide constructive operational semantics (implemented by us as an interpreter) for which the model is fully abstract. We show that the model is expressive by defining combinators from the synchronous languages. We show that Default cc is compositional and supports the properties of multiform time, orthogonal pre-emption and executable specifications. In addition, Default cc programs can be read as logical formulae (in an intuitionistic temporal logic)—we show that this logic is sound and complete for reasoning about (in)equivalence of Default cc programs. Like the synchronous languages, Default cc programs can be compiled into finite state automata. In addition, the translation can be specified compositionally. This enables separate compilation of Default cc programs and run-time tradeoffs between partial compilation and interpretation. A preliminary version of this paper was published as . (1995). Here we present a complete treatment of hiding, along with a detailed treatment of the model. Abstract This paper extends network-based methods of constraint satisfaction to include continuous variables, thus providing a framework for processing temporal constraints. In this framework, called temporal constraint satisfaction problem (TCSP), variables represent time points and temporal information is represented by a set of unary and binary constraints, each specifying a set of permitted intervals. The unique feature of this framework lies in permitting the processing of metric information, namely, assessments of time differences between events. We present algorithms for performing the following reasoning tasks: finding all feasible times that a given event can occur, finding all possible relationships between two given events, and generating one or more scenarios consistent with the information provided. We distinguish between simple temporal problems (STPs) and general temporal problems, the former admitting at most one interval constraint on any pair of time points. We show that the STP, which subsumes the major part of Vilain and Kautz's point algebra, can be solved in polynomial time. For general TCSPs, we present a decomposition scheme that performs the three reasoning tasks considered, and introduce a variety of techniques for improving its efficiency. We also study the applicability of path consistency algorithms as preprocessing of temporal problems, demonstrate their termination and bound their complexities. Temporal logic is two-valued: formulas are interpreted as either true or false. When applied to the analysis of stochastic systems, or systems with imprecise formal models, temporal logic is therefore fragile: even small changes in the model can lead to opposite truth values for a specification. We present a generalization of the branching-time logic CTL which achieves robustness with respect to model perturbations by giving a quantitative interpretation to predicates and logical operators, and by discounting the importance of events according to how late they occur. In every state, the value of a formula is a real number in the interval [0,1], where 1 corresponds to truth and 0 to falsehood. The boolean operators and and or are replaced by min and max, the path quantifiers ∃ and ¬ determine sup and inf over all paths from a given state, and the temporal operators ♦ and □ specify sup and inf over a given path; a new operator averages all values along a path. Furthermore, all path operators are discounted by a parameter that can be chosen to give more weight to states that are closer to the beginning of the path.We interpret the resulting logic DCTL over transition systems, Markov chains, and Markov decision processes. We present two semantics for DCTL: a path semantics, inspired by the standard interpretation of state and path formulas in CTL, and a fixpoint semantics, inspired by the µ-calculus evaluation of CTL formulas. We show that, while these semantics coincide for CTL, they differ for DCTL, and we provide model-checking algorithms for both semantics. We consider a state-dependent three-terminal full-duplex relay channel with the channel states noncausally available at only the source, that is, neither at the relay nor at the destination. This model has application to cooperation over certain wireless channels with asymmetric cognition capabilities and cognitive interference relay channels. We establish lower bounds on the channel capacity for both discrete memoryless (DM) and Gaussian cases. For the DM case, the coding scheme for the lower bound uses techniques of rate-splitting at the source, decode-and-forward (DF) relaying, and a Gel'fand-Pinsker-like binning scheme. In this coding scheme, the relay decodes only partially the information sent by the source. Due to the rate-splitting, this lower bound is better than the one obtained by assuming that the relay decodes all the information from the source, that is, full-DF. For the Gaussian case, we consider channel models in which each of the relay node and the destination node experiences on its link an additive Gaussian outside interference. We first focus on the case in which the links to the relay and to the destination are corrupted by the same interference; and then we focus on the case of independent interferences. We also discuss a model with correlated interferences. For each of the first two models, we establish a lower bound on the channel capacity. The coding schemes for the lower bounds use techniques of dirty paper coding or carbon copying onto dirty paper, interference reduction at the source and decode-and-forward relaying. The results reveal that, by opposition to carbon copying onto dirty paper and its root Costa's initial dirty paper coding (DPC), it may be beneficial in our setup that the informed source uses a part of its power to partially cancel the effect of the interference so that the uninformed relay benefits from this cancellation, and so the source benefits in turn.