21 results about "Logical formula" patented technology

The invention belongs to a specification mining technology of software engineering, and relates to a construction method of an approximate specification mining model and a software behavior verification system. The construction method comprises the following steps: generating a group of linear temporal logic LTL formulas for describing positive example time sequence attributes according to a positive example set; using an LTL formula to generate a potential negative example for evaluation and training; designing and constructing a neural network for analyzing the finite state automaton from the parameter assignment so as to simulate an acceptance behavior of the finite state automaton; and iteratively searching the neural network through a gradient descent algorithm until the maximum number of iterations is reached, and mining to obtain the finite state automaton. The neural network can simulate acceptance of the finite state automaton in the reasoning process, the finite state automaton can be explained at low cost, and the problem of search space explosion is solved.

This application discloses a puzzle generation method, apparatus, device, and readable storage medium. The method obtains a structured specification representation and seed parameters of a seed puzzle; generates a new problem using the seed parameters and the structured specification representation; verifies the accuracy of the structured specification representation using the new problem; if accurate, uses a puzzle generator to load the structured specification representation, reorganize the logical formula, and randomly sample specified data according to defined constraints to obtain a SMT problem; after verifying the SMT problem's logical reliability and solvability using a solver, obtains new configuration parameters based on the SMT problem; fills the new configuration parameters into the structured specification representation and renders it using a natural language template to obtain a target puzzle with a problem instance and a standard answer. This application, through pre-coding, reproducing, and verifying puzzles, can automatically generate accurate and reliable new puzzles in batches.

The temporal logic formula generation device 1X mainly includes a target relation logical formula generation means 331X and a target relation logical formula integration means 332X. The target relation logical formula generation means 331X is configured to generate, based on object-to-object relation information representing a relation between objects in a target state relating to a task of the robot, one or more target relation logical formulas that are temporal logic formulas representing relations, in the target state, between respective pair(s) of objects between which the relation is defined. The target relation logical formula integration means 332X is configured to generate a temporal logic formula into which the target relation logical formulas are integrated.

A logical formula generation device 100 according to the present invention comprises: a planning means 121 for, on the basis of background knowledge information indicating a rule of inference, input information to be subjected to an inference process by the rule of inference, an inference schema indicating an inference method in the inference process, and a concept schema indicating a concept to be addressed in the inference process, generating a logical conversion protocol for converting the background knowledge information and the input information to a logical formula; and a conversion means 122 for converting the background knowledge information and the input information to a logical formula on the basis of the generated logical conversion protocol.

A constraint condition learning device 1X mainly includes a conversion means 15X and a constraint condition estimation means 16X. The conversion means 15X converts first time series data regarding a state and an input of a robot system during an execution period of a task executed by the robot system into second time series data represented by propositions. The constraint condition estimation means 16X estimates a constraint condition on the task as a logical formula, based on the second time series data and the information regarding whether or not the task succeeded.

In one embodiment, a method comprises: parsing, using a large language model, a constraint satisfaction problem statement into a sequence of sentences corresponding to a plurality of individual problem sentences and a plurality of individual answer choices; invoking respective primitives from a set of logical-linguistic primitive functions to iteratively process i) each of the plurality of individual problem sentences to establish a respective problem constraint with accompanying arguments and ii) each of the plurality of individual answer choices to establish a respective answer choice constraint with accompanying arguments; storing, during invoking, the respective problem constraints into an aggregate list of problem constraints; and solving, after completion of the aggregate list of problem constraints, the constraint satisfaction problem statement as a validity output for each answer choice constraint given the aggregate list of problem constraints.

This invention discloses a method for automatically generating power system anti-misoperation logic formulas, comprising: acquiring Public Information Model (CIM) data of target sites in a power system; matching power equipment with a first logical relationship data table in an anti-misoperation logic knowledge base to determine the location feature information corresponding to the power equipment; matching the location feature information corresponding to the power equipment with a second logical relationship data table in multiple logical relationship data tables to determine multiple logical rule description information corresponding to the power equipment; matching the multiple logical rule description information corresponding to the power equipment with a third logical relationship data table in multiple logical relationship data tables to generate logical rule element information corresponding to the power equipment; and combining the logical rule element information matched by each power equipment according to a preset format to obtain the anti-misoperation logic formula for the target site. This invention solves the problems of low generation efficiency and accuracy of anti-misoperation logic formulas, and inconvenience in maintenance, modification, and review.

The application discloses a project whole-process penetration control method and system based on multi-source data fusion, and relates to the technical field of engineering project risk control and time sequence logic formal verification. The method comprises the following steps: acquiring a control instruction generated by a multi-agent cooperation system; extracting an attention weight distribution in an inference process to lock a target subgraph in a fusion knowledge graph, and cutting a global compliance rule to obtain a local formal context according to the target subgraph; mapping numerical variables in the local formal context into interval logic operators and constructing a local linear time sequence logic formula; and performing safety verification on the formula, and executing the control instruction when the formula passes the safety verification. The application is used to solve the problems of instruction illusion risk caused by the probabilistic decision of the generative model and the calculation space explosion caused by the global system state verification.

A system for converting natural language (NL) requirements of an aerospace system to formalize to control a landing gear system of an aircraft using a large language model (LLM) includes a processor and a memory including instructions that, when executed by the processor, convert the NL requirements into formalities to control the landing gear system of the aircraft. The system is caused to use at least the LLM to revise the received NL expressions associated with the requirements of the aerospace system. The LLM is further configured to replace at least one word in the revised NL expression with a lifting atomic entity to generate an underlying sentence structure and convert the underlying sentence structure into a lifting logic. The LLM is also used for basic improvement of the logical expression and conversion of the NL expression into formalized requirements of an aerospace system. The system also controls the aerospace system based on the formal demand.

A system for using large language models (LLMs) to convert natural language (NL) requirements for aerospace systems to formalism for controlling a landing gear system of an aircraft includes a processor and a memory including instructions which, when executed by the processor, causes the system at least to perform using an LLM to revise a received NL expression associated with a requirement for an aerospace system. An LLM is also used to replace at least one word in the revised NL expression with a lifted atomic entity to generate an underlying sentence structure and translate the underlying sentence structure to a lifted logical formula. An LLM is also used to ground the lifted logical formula and to convert the NL expression into a formalized requirement for the aerospace system. The system also controls the aerospace system based on the formalized requirement.

The present application relates to a kind of test script intelligent generation method and system of substation anti-misoperation dynamic check.Test method is: the content of substation interlocking logic diagram or anti-misoperation acceptance card is extracted and the anti-misoperation logic formula of fixed format is generated;Operation order is generated based on the anti-misoperation logic formula and covers positive and negative direction full acceptance;Through text matching large model, in 103 communication text, 104 point table or SCD configuration file, the path or point number matched with each description object in operation order is found and associated, to generate the first edition substation anti-misoperation dynamic check test script;Self-check is carried out to the first edition substation anti-misoperation dynamic check test script, to obtain accurate substation anti-misoperation dynamic check test script.The system includes anti-misoperation interlocking logic analysis module, anti-misoperation operation order automatic generation module, three remote signal automatic association module, anti-misoperation check script self-checking module connected in turn.The present application can guarantee the quality of substation anti-misoperation dynamic check, improve check efficiency.

A method for managing an Operational Design Domain (ODD) expansion for an Automated Driving System (ADS) of a vehicle is disclosed. The method includes: obtaining a plurality of scenario parameters defining the environment of the vehicle, wherein each scenario parameter corresponds to a respective condition of the ODD; in response to the plurality of scenario parameters fulfilling the plurality of ODD conditions: allowing the ADS to be activated or to remain active; if not: querying a logic formula based on the obtained plurality of scenario parameters, such that if at least one soft constraint of the logical formula is satisfied without violating any hard constraints of the logical formula, and allowing the ADS to be activated in a degraded mode by limiting one or more variable state parameters of the ADS to conform to the determined set of values of the one or more variable state parameters.

The application discloses a kind of based on big model's safety key software verification property automatic generation method, comprising: extracting subject and predicate from each atomic proposition, the subject and predicate extracted are merged, and the atomic proposition after reorganization is obtained;Define non-standard natural language type template;According to the defined non-standard natural language type template, the reorganized atomic proposition is combined with logic operator using random algorithm, to generate signal timing logic formula;And using big language model, it is translated into natural language, to build the data set containing formula-natural language pair;According to the situation, use the data set containing formula-natural language pair to fine-tune local big model or big language model interface, obtain the big model after fine-tuning;Using prompt word template, the natural language requirement to be translated is input into the big model after fine-tuning, to obtain corresponding timing logic formula.

The invention relates to the technical field of safety verification of robot operating systems, in particular to a robot monitoring node automatic generation method based on a structured natural language. The method comprises the following steps: acquiring a structured natural language monitoring requirement; analyzing and converting the data into a probability sequential logic formula and a variable mapping relation; verifying whether the variable exists in the target data stream framework or not; and automatically generating a monitoring node capable of running in the data stream framework based on the verified formula and the mapping relation. And when the monitoring node runs, monitoring variable update, and only triggering conformity judgment of the correlation formula. The problems that in the prior art, requirement conversion is difficult, monitoring logic and a platform are strongly coupled, and execution time is unpredictable are solved, and requirement unambiguous formalization and monitoring code full-automatic generation are achieved.

Embodiments provide graphical representations of logical formulae. An example embodiment includes, based on logical scopes from a logical formula, partitioning a graphical space using one or more graphical elements. Tables are placed in the graphical spaced partitioned. At least one table placed includes a table reference based on the logical scopes and a table attribute based on predicates from the logical formula. Based on the predicates and the logical scopes, at least one connection is displayed between the tables placed. The at least one connection indicates a given predicate, and a logical scope of the given predicate is independent of endpoints of the at least one connection. The graphical space partitioned, the tables placed, and the at least one connection displayed provide a graphical representation of the logical formula. Embodiments may provide diagrammatic representations of queries including disjunctions, aggregations, or assignments for human and machine use.

A system for using large language models (LLMs) to convert natural language (NL) requirements for aerospace systems to formalism for controlling a landing gear system of an aircraft includes a processor and a memory including instructions which, when executed by the processor, causes the system at least to perform using an LLM to revise a received NL expression associated with a requirement for an aerospace system. An LLM is also used to replace at least one word in the revised NL expression with a lifted atomic entity to generate an underlying sentence structure and translate the underlying sentence structure to a lifted logical formula. An LLM is also used to ground the lifted logical formula and to convert the NL expression into a formalized requirement for the aerospace system. The system also controls the aerospace system based on the formalized requirement.

The application provides a kind of explainable fault diagnosis system and method of discrete event system, adopts the calculation mode of combining off-line construction fault diagnosis device and on-line fault diagnosis, while fusing field expert knowledge, according to the possible mode of system fault given by field expert, customizes limited linear time logic formula template, takes the historical operation log of system as sample, encodes fault diagnosis problem as satisfiability problem, obtains the explanation of each type of fault behavior of system: FLTL formula with the help of SAT solving technique.These FLTL formulas can form on-line fault diagnosis device on the one hand, and also provide the explanation and analysis of system fault, which can provide decision support for later system fault recovery and system improvement;Thus, the defect that existing DES fault diagnosis technology is difficult to provide explainable fault diagnosis is solved.

An analysis apparatus includes an inputter configured to receive an input of a first temporal logic formula and an input of a second temporal logic formula, and an outputter configured to output a screen for displaying a first block diagram showing the first temporal logic formula and a second block diagram showing the second temporal logic formula in a comparable manner.

The information processing device 1A mainly includes a logical formula conversion unit 322A, a constraint condition information acquisition unit 323A, and a constraint condition addition unit 324A. The logical formula conversion unit 322A is configured to convert an objective task, which is a task to be performed by a robot, into a logical formula that is based on a temporal logic. The constraint condition information acquisition unit 323A is configured to acquire constraint condition information I2 indicative of a constraint condition to be satisfied in performing the objective task. The constraint condition addition unit 324A is configured to generate a target logical formula Ltag that is a logical formula obtained by adding a proposition indicative of the constraint condition to the logical formula generated by the logical formula conversion unit 322A.

A logical formula generation apparatus of the present invention includes: a planning means for generating a logical transformation protocol for transforming background knowledge information and input information into logical formulas based on the background knowledge information, the input information, a reasoning schema and a conceptual schema, the background knowledge information representing a reasoning rule, the input information being subjected to a reasoning process by the reasoning rule, the reasoning schema representing a reasoning mode in the reasoning process, the conceptual schema representing a concept handled in the reasoning process; and a transforming means for transforming the background knowledge information and the input information into logical formulas based on the generated logical transformation protocol.

In various examples, systems and methods are disclosed related to facilitating management of evaluator logic. In particular, evaluator logic is generated in association with a requirement in an effective and efficient manner. To efficiently generate evaluator logic, artificial intelligence (AI) technology may be used to perform various aspects of the evaluator logic generation. In particular, a logical formula that represents the requirement may be generated using a temporal logic. The logical formula may then be used to generate, via one or more machine learning models, an evaluator logic in an executable format. In accordance with efficiently generating evaluator logic, the evaluator logic may be implemented to evaluate a product, a system, or other technology.