Abstract: An information processing apparatus and an information processing method capable of accurately recognizing an object to be sensed are provided. One or a plurality of learning models are selected from among learning models corresponding to a plurality of categories, a priority of each of the selected learning models is set, observation data obtained by sequentially compounding pieces of sensor data applied from a sensor is analyzed using the learning model and the priority of the learning model, a setting of sensing at a next cycle is selected based on an analysis result, predetermined control processing is executed in such a manner that the sensor performs sensing at the selected setting of sensing, and the learning model corresponding to the category estimated as the category to which a current object to be sensed belongs with a highest probability is selected based on the categories to each of which the previously recognized object to be sensed belongs.

Abstract: An autonomous distributed coordination system is provided which is intended to be used for a broad-area search in an unknown environment without the need for a prior plan and map sharing.

Abstract: To generate a prediction image in which an outline of an object is clear and existence of the object is easily recognized, the image prediction system that generates a future prediction image and includes a gaze unit, a working memory unit, a control unit, and a generation model unit. The gaze unit controls a region including an object included in an observation image as a first gaze region. The working memory unit controls the first gaze region as a second gaze region when a difference in the first gaze region between the observation image and a prediction image is equal to or less than a predetermined value. The generation model unit generates prediction images of the first gaze region and the second gaze region. The control unit integrates the prediction image of the first gaze region and the prediction image of the second gaze region to generate a prediction image.

Abstract: A retail agent determines a parameter of an activity proposal model by using data stored in a past record database, and determines parameters of an activity determination model and an activity value evaluation model by further using base activity simulation data. Consequently, it is possible to appropriately determine parameters of a subsystem control method in a complex system which cannot be embodied as a simulator and shows a significant change with respect to past record data.

Abstract: A computer system that supports design for improving a function of a biological resource registers a history of the design, the history of the design including pair information of a related element related to a property of the biological resource and an operation on the related element, searches a database based on the pair information, acquires additional information other than the related element, the additional information being information related to the property of the biological resource based on a result of the search, computes a correlation of the additional information to the related element, and evaluates the additional information based on the calculated correlation.

Abstract: An information processing apparatus and an information processing method capable of accurately recognizing an object to be sensed are provided. One or a plurality of learning models are selected from among learning models corresponding to a plurality of categories, a priority of each of the selected learning models is set, observation data obtained by sequentially compounding pieces of sensor data applied from a sensor is analyzed using the learning model and the priority of the learning model, a setting of sensing at a next cycle is selected based on an analysis result, predetermined control processing is executed in such a manner that the sensor performs sensing at the selected setting of sensing, and the learning model corresponding to the category estimated as the category to which a current object to be sensed belongs with a highest probability is selected based on the categories to each of which the previously recognized object to be sensed belongs.

Abstract: To generate a prediction image in which an outline of an object is clear and existence of the object is easily recognized, the image prediction system that generates a future prediction image and includes a gaze unit, a working memory unit, a control unit, and a generation model unit. The gaze unit controls a region including an object included in an observation image as a first gaze region. The working memory unit controls the first gaze region as a second gaze region when a difference in the first gaze region between the observation image and a prediction image is equal to or less than a predetermined value. The generation model unit generates prediction images of the first gaze region and the second gaze region. The control unit integrates the prediction image of the first gaze region and the prediction image of the second gaze region to generate a prediction image.

Abstract: According to one embodiment, a machine control system includes: a selecting unit which acquires a state quantity of a machine converted from data acquired by a sensor provided in the machine to select two or more learning models according to the acquired state quantity; a composing unit which inputs the state quantity acquired by the selecting unit to each of the two or more learning models selected by the selecting unit to calculate a composed value using a command value output from each of the learning models; and a learning unit which outputs a command value with respect to the machine in a range based on the composed value calculated by the composing unit, acquires a state quantity of the machine, searches for a command value of a specific condition from a combination of the output command value and the acquired state quantity, and outputs the searched command value to the machine, thereby creating a new learning model.

Abstract: An information processing system, in which information related to an input metabolic pathway is input, includes: a main metabolic map including a pathway most similar to or the same as the input metabolic pathway is selected from a database of a metabolic map represented by a directed graph in which a compound that is a reaction compound in a metabolic reaction is set as a node, and an enzyme that acts when a node used in reaction is moved to a node produced by reaction is set as an edge, a compound in a vicinity of the input metabolic pathway is selected from the main metabolic map as a peripheral compound, and a search expression is generated based on information on the selected peripheral compound and information of the compound and enzyme related to the input metabolic pathway so as to search the literature database for a literature.

Abstract: A method for making a recombinant gene includes searching a database using a nucleotide sequence of a coding region, a nucleotide sequence that encodes an amino acid sequence, or an amino acid sequence, of a gene, for one or more nucleotide sequences having homology; selecting one or more nucleotide sequences other than nucleotide sequences only derived from a genome from the selected nucleotide sequences; for ones of the selected one or more nucleotide sequences comprising an upstream or downstream nucleotide sequence, analyzing whether the upstream or downstream nucleotide sequence is a functional sequence to select one or more first functional sequences; for ones of the selected one or more nucleotide sequences comprising no upstream or downstream nucleotide sequence, analyzing whether a gene information has any description indicating a functional sequence to select one or more second functional sequences; scoring the selected functional sequences; and selecting one or more functional sequences.

Abstract: To predict a new biological reaction by quantifying while retaining characteristics of an entire compound structure. To provide a structural characteristic amount encoding unit that includes a conversion model unit configured to convert a characteristic amount of notation information indicating chemical structures of a plurality of compounds into a dispersedly represented numerical vector having at least two or more real number values as an element using a conversion parameter, the conversion model unit converting the characteristic amount of the notation information indicating the chemical structures into a numerical vector, for each of a first compound and a second compound among the plurality of compounds, and a biological reaction characteristic vector generator configured to generate a biological reaction characteristic vector between the first compound and the second compound by performing a calculation using a numerical vector of the first compound and a numerical vector of the second compound.

Abstract: A learning control system is provided in each of a plurality of subsystems of a system and includes a plurality of agents that performs learning to control of the subsystem using a control model and a learning management agent that manages and controls learning of each of the plurality of agents. The learning management agent is operated with a plurality of experiment systems including the plurality of control model sets of the plurality of agents and determines a plurality of updating control model sets in the plurality of experiment systems of a next generation from an evaluation result of the plurality of experiment systems of the current generation. The agent transmits control model information of a current generation to the learning management agent and receives control model information of the next generation from the learning management agent.

Abstract: An information processing system includes a storing unit that stores evaluation data in which a plurality of subjects are associated with a plurality of evaluation expressions respectively and evaluation expression relationship data indicating relationships between the evaluation expressions, a question generating unit that generates and outputs questions on the basis of the evaluation data and the evaluation expression relationship data, and a matching unit that outputs information relating to the subject included in the evaluation data on the basis of responses when the responses with respect to the questions are input.

Abstract: A retail agent determines a parameter of an activity proposal model by using data stored in a past record database, and determines parameters of an activity determination model and an activity value evaluation model by further using base activity simulation data. Consequently, it is possible to appropriately determine parameters of a subsystem control method in a complex system which cannot be embodied as a simulator and shows a significant change with respect to past record data.

Abstract: The control device includes: an observation unit that calculates an amount relating to a state of a control target detected by a sensor; an abnormality predictor detection unit that detects an abnormality predictor of the control target; a reward calculation unit that calculates a reward which is an amount obtained by evaluating pass or fail of an operation of the control target; a basic control amount calculation unit that calculates data relating to the state during an operation and a basic control amount serving as a reference to control the control target; a control amount search unit that searches for a control amount at which the reward satisfies a predetermined condition based on the basic control amount, the data relating to the state during the operation and the reward; and a control unit that generates a command value to the control target.

Abstract: The control device includes: an observation unit that calculates an amount relating to a state of a control target detected by a sensor; an abnormality predictor detection unit that detects an abnormality predictor of the control target; a reward calculation unit that calculates a reward which is an amount obtained by evaluating pass or fail of an operation of the control target; a basic control amount calculation unit that calculates data relating to the state during an operation and a basic control amount serving as a reference to control the control target; a control amount search unit that searches for a control amount at which the reward satisfies a predetermined condition based on the basic control amount, the data relating to the state during the operation and the reward; and a control unit that generates a command value to the control target.

Abstract: According to one embodiment, a machine control system includes: a selecting unit which acquires a state quantity of a machine converted from data acquired by a sensor provided in the machine to select two or more learning models according to the acquired state quantity; a composing unit which inputs the state quantity acquired by the selecting unit to each of the two or more learning models selected by the selecting unit to calculate a composed value using a command value output from each of the learning models; and a learning unit which outputs a command value with respect to the machine in a range based on the composed value calculated by the composing unit, acquires a state quantity of the machine, searches for a command value of a specific condition from a combination of the output command value and the acquired state quantity, and outputs the searched command value to the machine, thereby creating a new learning model.

Abstract: A learning control system is provided in each of a plurality of subsystems of a system and includes a plurality of agents that performs learning to control of the subsystem using a control model and a learning management agent that manages and controls learning of each of the plurality of agents. The learning management agent is operated with a plurality of experiment systems including the plurality of control model sets of the plurality of agents and determines a plurality of updating control model sets in the plurality of experiment systems of a next generation from an evaluation result of the plurality of experiment systems of the current generation. The agent transmits control model information of a current generation to the learning management agent and receives control model information of the next generation from the learning management agent.

Abstract: A control device that determines an output value of an actuator based on an input value of a sensor, includes a control unit that includes a control model capable of changing a parameter; a control unit that includes a control model fixed in a parameter acquired by a different device; and an action selection unit that selects an output value from output values of the respective control units and outputs the selected output value to an actuator, and determines an output value of the actuator, based on an input value from a sensor of a machine.

Abstract: An information processing system includes a storing unit that stores evaluation data in which a plurality of subjects are associated with a plurality of evaluation expressions respectively and evaluation expression relationship data indicating relationships between the evaluation expressions, a question generating unit that generates and outputs questions on the basis of the evaluation data and the evaluation expression relationship data, and a matching unit that outputs information relating to the subject included in the evaluation data on the basis of responses when the responses with respect to the questions are input.