Abstract: A tailored interactive language learning system that teaches an individualized set of vocabulary words to users through interactive avatars and stories. The interaction is modeled through probabilistic rules in a semantic network and neural network having objects and relations. Dialog and narration is generated dynamically based on the state of the interactive story model using phrasal rewrite rules and neural network implementing a four-valued logic system in which truth values of the objects and relations are encoded as true, false, defined, and undefined in a single memory array.

Abstract: A language learning system that teaches an individualized set of vocabulary words to users through an interactive story. The interactive story is modeled through probabilistic rules in a semantic network having objects and relations. Dialog and narration is generated dynamically based on the state of the interactive story model using phrasal rewrite rules evaluated with a four-valued logic system in which truth values of the objects and relations are encoded as true, false, defined, and undefined in parallel memory structures.

Abstract: A language learning system that teaches an individualized set of vocabulary words to users through an interactive story. The interactive story is modeled through probabilistic rules in a semantic network having objects and relations. Dialog and narration is generated dynamically based on the state of the interactive story model using phrasal rewrite rules evaluated with a four-valued logic system in which truth values of the objects and relations are encoded as true, false, defined, and undefined in parallel memory structures.

Abstract: A four-valued logic system for genomic sequencing and macromolecular analysis using a semantic network having object nodes and relationships between the object nodes. The object nodes are each represented by two vectors with true, false, defined, or undefined values in corresponding bits in the two vectors. Conditionals or quantifying variables are tested during successive recursive steps in a predicate calculus using the four-valued logic system.

Abstract: A system for the dynamic encoding in a semantic network of both syntactic and semantic information into a common four valued logical notation. The encoding of new information being benign to prior syntactic constructions, tests for N conditionals in time O(C) and allows for the proper quantification of variables at each recursive step. The query/inference engine constructed from such an implementation is able to optimize short term memory for maximizing long term storage in the automaton. In a parallel context this can be viewed as optimizing communication and memory allocation between processes. Disclosed embodiments of a four valued encoding achieve efficiencies in minimizing the run time stack and maximizing heap size especially in a parallel architecture. Disclosed embodiments are useful in simulation and search engine implementations.

Abstract: Automatic trading environments with their high degree of automation have become the backbone of modern financial markets. The ability to process orders and manage risk in these systems while maintaining a low latency between participants is crucial for the safety and liquidity of these markets. The disclosed system describes a four valued Monte Carlo simulation for the stochastic modeling of risk and syntactic pattern matching techniques to facilitate the design of these systems. The system is a self-compiling, machine independent system capable of dividing, scaling and communicating multiple-asset instruments efficiently in a parallel environment. The system also allows for the integration of computerized financial heuristics on financial instruments and user interfaces for creating trading strategies to monitor and hedge risk over a trading desk for financial institutions.

Abstract: A system for the dynamic encoding in a semantic network of both syntactic and semantic information into a common four valued logical notation. The encoding of new information being benign to prior syntactic constructions, tests for N conditionals in time O(C) and allows for the proper quantification of variables at each recursive step. The query/inference engine constructed from such an implementation is able to optimize short term memory for maximizing long term storage in the automaton. In a parallel context this can be viewed as optimizing communication and memory allocation between processes. The self-referencing system is capable of analogically extending knowledge from one knowledge source to another linearly. Disclosed embodiments include machine translation, text summarization, natural language speech recognition natural language.

Abstract: Automatic trading environments with their high degree of automation have become the backbone of modern financial markets. The ability to process orders and manage risk in these systems while maintaining a low latency between participants is crucial for the safety and liquidity of these markets. The disclosed system describes a four valued Monte Carlo simulation for the stochastic modeling of risk and syntactic pattern matching techniques to facilitate the design of these systems. The system is a self-compiling, machine independent system capable of dividing, scaling and communicating multiple-asset instruments efficiently in a parallel environment. The system also allows for the integration of computerized financial heuristics on financial instruments and user interfaces for creating trading strategies to monitor and hedge risk over a trading desk for financial institutions.

Abstract: A system for the dynamic encoding in a semantic network of both syntactic and semantic information into a common four valued logical notation. The encoding of new information being benign to prior syntactic constructions, tests for N conditionals in time O(C) and allows for the proper quantification of variables at each recursive step. The query/inference engine constructed from such an implementation is able to optimize short term memory for maximizing long term storage in the automaton. In a parallel context this can be viewed as optimizing communication and memory allocation between processes. The self-referencing system is capable of analogically extending knowledge from one knowledge source to another linearly. Disclosed embodiments include machine translation, text summarization, natural language speech recognition natural language.

Abstract: A four valued parallelized simulation with the ability to implement computer systems with the ability to combine a mixture of computer intensive techniques in DNA analysis and molecular crystallography. Disclosed systems and methods aid in the design of drugs, pharmaceutical research, genetically modified organisms and the detection of genetic sequences for gene therapy.

Abstract: A system for the dynamic encoding in a semantic network of both syntactic and semantic information into a common four valued logical notation. The encoding of new information being benign to prior syntactic constructions, tests for N conditionals in time O(C) and allows for the proper quantification of variables at each recursive step. The query/inference engine constructed from such an implementation is able to optimize short term memory for maximizing long term storage in the automaton. In a parallel context this can be viewed as optimizing communication and memory allocation between processes. Disclosed embodiments of a four valued encoding achieve efficiencies in minimizing the run time stack and maximizing heap size especially in a parallel architecture. Disclosed embodiments are useful in simulation and search engine implementations.