We present a domain-specific imperative language, Bek, that directly models low-level string manipulation code featuring boolean state, search operations, and substring substitutions. We show constructively that Bek is reversible through a semantics-preserving translation to symbolic finite state transducers, a novel representation for transducers that annotates transitions with logical formula...

Although the relationship between sound and meaning in language is arbitrary, reliable correspondences between sound and meaning have been found in natural language. These sound symbolic relationships affect word learning, but less is known about how sound symbolism affects online processing during learning or for well-learned stimuli. We use the visual world paradigm and an artificial lexicon ...

Evolution of symbolic language and grammar is studied in a network model. Language is expressed by words, i.e. strings of symbols, which are generated by agents with their own symbolic grammar system. Agents communicate with each other by deriving and accepting words via rewriting rule set. They are ranked according to their communicative effectiveness: an agent which can derive less frequent a...

We present a declarative intermediate language KIL in a symbolic executor for C++ programs and show how to use KIL to control symbolic execution. KIL is an abstract language defined over LLVM bytecode; it provides a higher level model of C++ object operations and functions. KIL enables lazy function evaluation, object-level execution and reasoning, defining built-in efficient solvers, function ...

Classification is a frequently encountered data mining problem. While symbolic classifiers have high comprehensibility, their language bias may hamper their classification performance. Incorporating new features constructed based on the original features may relax such language bias and lead to performance improvement. Among others, principal component analysis (PCA) has been proposed as a poss...

Automatic methods developed so far for analysis of security protocols only model a limited set of cryptographic primitives (often, only encryption and concatenation) and abstract from low-level features of cryptographic algorithms. This paper is an attempt towards closing this gap. We propose a symbolic technique and a decision method for analysis of protocols based on modular exponentiation, s...

Automatic methods developed so far for analysis of security protocols only model a limited set of cryptographic primitives (often, only encryption and concatenation) and abstract from low-level features of cryptographic algorithms. This paper is an attempt towards closing this gap. We propose a symbolic technique and a decision method for analysis of protocols based on modular exponentiation, s...

A theoretical framework for grounding language is introduced that provides a computational path from sensing and motor action to words and speech acts. The approach combines concepts from semiotics and schema theory to develop a holistic approach to linguistic meaning. Schemas serve as structured beliefs that are grounded in an agent’s physical environment through a causal-predictive cycle of a...

Many machine reading approaches, from shallow information extraction to deep semantic parsing, map natural language to symbolic representations of meaning. Representations such as first-order logic capture the richness of natural language and support complex reasoning, but often fail in practice due to their reliance on logical background knowledge and the difficulty of scaling up inference. In...

We integrate a verified typechecker with a verified program logic for the C language, proved sound with respect to the operational semantics of the CompCert verified optimizing C compiler. The C language is known to not be type-safe but we show the value of a provably mostly sound type system: integrating the typechecker with the program logic makes the logic significantly more usable. The comp...