Symbolic finite automata extend classical automata by allowing infinite alphabets given by Boolean algebras and having transitions labeled by predicates over such algebras. Symbolic automata have been intensively studied recently and they have proven useful in several applications. We study some theoretical aspects of symbolic automata. Especially, we study minterms of symbolic automata, that i...

A symbolic compiler translates a program to symbolic constraints, automatically reducing model checking and synthesis to constraint solving. We show that new applications of constraint solving require domain-specific encodings that yield orders of magnitude improvements in solver efficiency. Unfortunately, these encodings cannot be obtained with today’s symbolic compilation. We introduce symbol...

Symbolic execution of a language is traditionally achieved by replacing the language’s interpreter with an entirely new interpreter. This may be an unnecessary burden, and it is tempting instead to try to use as much of the existing interpret infrastructure as possible, both for handling aspects of the computation that are not symbolic, and for propagating symbolic ones. This approach was used ...

We present SAM, a symbolic model checker for ACTL, the action-based version of CTL. SAM relies on implicit representations of Labeled Transition Systems (LTSs), the semantic domain for ACTL for-mulae, and uses symbolic manipulation algorithms. SAM has been realized by translating (networks of) LTSs and, possibly recursive, ACTL formulae into BSP (Boolean Symbolic Programming), a programming lan...

We present an approach which enables an agent to learn to achieve goals in continuous environments using a symbolic architecture. Symbolic processing has an advantage over numerical regression techniques because it can interface more easily with other symbolic systems, such as systems for natural language and planning. Our approach is to endow an agent with qualitative “seed” knowledge and allo...

This thesis examines distributional and contextual aspects of linguistic processing in relation to traditional symbolic approaches. Distributional processing is more commonly associated with statistical methods, while an integrated representation of context spanning document and syntactic structure is lacking in current linguistic representations. This thesis addresses both issues through a nov...

This paper presents a statistical/symbolic hybrid morphological analysis, called V-morph, for large scale speech and natural language integration for Korean. In the V-morph approach, statistical Viterbi-based lexical decoding and symbolic morphological modeling are integrated together on top of connectionist phoneme recognition engine. Linguistic characteristics of Korean are appropriately cons...

ferdowsi’s shāhnāma has a monotheistic context and its narrative deep structure has been demythologized throughout history at religious, ritual and mythic levels. however, an analytical approach can spot traces of the ancient beliefs reflected in the symbolic implications of the narratives as well as the language and imagery of the shāhnāma. the first line in the preface of the shāhnāma, “in th...

Previous approaches of analyzing spontaneously spoken language often have been based on encoding syntactic and semantic knowledge manually and symbolically. While there has been some progress using statistical or connectionist language models, many current spoken-language systems still use a relatively brittle, hand-coded symbolic grammar or symbolic semantic component. In contrast, we describe...