This paper provides a survey on probabilistic decision graphs for modeling and solving decision problems under uncertainty. We give an introduction to influence diagrams, which is a popular framework for representing and solving sequential decision problems with a single decision maker. As the methods for solving influence diagrams can scale rather badly in the length of the decision sequence, ...

Hybrid automata are the prevailing formalisms to reason about systems that consist of discrete and continuous functions. Several specializations like o-minimal hybrid automata have been considered that should (1) retain as much expressibility as possible, and (2) lead to decidable (reachability) problems. However, the discrete transitions of o-minimal automata require constant resets of the con...

Various forms of rely/guarantee conditions have been used to record and reason about interference in ways that provide compositional development methods for concurrent programs. This paper illustrates such a set of rules and proves their soundness. The underlying concurrent language allows fine-grained interleaving and nested concurrency; it is defined by an operational semantics; the proof tha...

There is an increasing trend towards parallel processing and data processing using cloud environments. Simple APIs for expressing parallelism, such as map-reduce, are popular in cloud environments, but their expressibility is generally considered limited. This paper focuses on how a signal processing algorithm, wavelet transform, can be parallelized in a cloud environment comprising a cluster o...

Natural language processing often involves computations with semantic or syntactic graphs to facilitate sophisticated reasoning based on structural relationships. While convolution kernels provide a powerful tool for comparing graph structure based on node (word) level relationships, they are difficult to customize and can be computationally expensive. We propose a generalization of convolution...

We introduce quantified interpreted systems, a semantics to reason about knowledge in multi-agent systems in a first-order setting. Quantified interpreted systems may be used to interpret a variety of first-order modal epistemic languages with global and local terms, quantifiers, and individual and distributed knowledge operators for the agents in the system. We define first-order modal axiomat...

Many learning systems must confront the problem of run time after learning being greater than run time before learning. This utility problem has been a particular focus of research in explanation-based learning. In past work we have examined an approach to the utility problem that is based on restricting the expressiveness of the rule language so as to guarantee polynomial bounds on the cost of...

Conceptual Programming is a term meant to convey a similar idea to that of Logic Programming, but at a higher level of representation. Programming with concepts, as presented here, has all the advantages that many knowledge representation schemes have in dealing with declarative knowledge i.e. explicitness, naturalness, expressibility, and transparency. It also gives procedural knowledge these ...

Abstract The Large Hadron Collider (LHC) at the European Organisation for Nuclear Research (CERN) will be upgraded to further increase instantaneous rate of particle collisions (luminosity) and become High Luminosity LHC (HL-LHC). This in luminosity significantly number particles interacting with detector. interaction a detector is referred as “hit”. HL-LHC yield many more hits, which pose comb...

<span lang="EN-US">Extensible markup language (XML) is well-known as the standard for data exchange over Internet. It flexible and has high expressibility to express relationship between stored. Yet, structural complexity semantic relationships are not well expressed. On other hand, ontology models structural, domain knowledge effectively. By combining with visualization effect, one will ...