Information processing apparatus, information processing method, and program
First Claim
1. An information processing apparatus comprising:
- connection network storage means for storing a connection network which includes a first self-organization map and a second self-organization map each including a plurality of nodes and which also includes connection weights indicating connection strengths of nodes between the first self-organization map and the second self-organization map;
first learning means for learning the first self-organization map, based on a first parameter extracted from an observed value output by observation means that observes an external world and outputs the observed value;
winner node determination means for detecting a node having highest likelihood that the first parameter is observed at the node in the first self-organization map and determining the detected node as a winner node;
searching means for searching the second self-organization map for a node having highest connection strength with the winner node and employing the detected node as a generation node;
parameter generation means for generating a second parameter from the generation node;
modification means for modifying the second parameter generated from the generation node;
determination means for determining whether an end condition is satisfied to end modification of the second parameter, the modification being performed in accordance with the winner node determined for a value which is observed by the observation means when driving means performs a driving operation in accordance with the second parameter;
first connection weight modification means for modifying the connection weight when the end condition is satisfied;
second connection weight modification means for modifying the connection weight when evaluation by a user on the result of driving performed by the driving means is given as a reward by the user; and
second learning means for learning the second self-organization map based on the second parameter obtained when the end condition is satisfied.
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Abstract
An information processing apparatus includes a first learning unit adapted to learn a first SOM (self-organization map), based on a first parameter extracted from an observed value, a winner node determination unit adapted to determine a winner node on the first SOM, a searching unit adapted to search for a generation node on a second SOM having highest connection strength with the winner node, a parameter generation unit adapted to generate a second parameter from the generation node, a modification unit adapted to modify the second parameter generated from the generation node, a first connection weight modification unit adapted to modify the connection weight when end condition is satisfied, a second connection weight modification unit adapted to modify the connection weight depending on evaluation made by a user, and a second learning unit adapted to learn the second SOM based on the second parameter obtained when the end condition is satisfied.
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Citations
7 Claims
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1. An information processing apparatus comprising:
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connection network storage means for storing a connection network which includes a first self-organization map and a second self-organization map each including a plurality of nodes and which also includes connection weights indicating connection strengths of nodes between the first self-organization map and the second self-organization map;
first learning means for learning the first self-organization map, based on a first parameter extracted from an observed value output by observation means that observes an external world and outputs the observed value;
winner node determination means for detecting a node having highest likelihood that the first parameter is observed at the node in the first self-organization map and determining the detected node as a winner node;
searching means for searching the second self-organization map for a node having highest connection strength with the winner node and employing the detected node as a generation node;
parameter generation means for generating a second parameter from the generation node;
modification means for modifying the second parameter generated from the generation node;
determination means for determining whether an end condition is satisfied to end modification of the second parameter, the modification being performed in accordance with the winner node determined for a value which is observed by the observation means when driving means performs a driving operation in accordance with the second parameter;
first connection weight modification means for modifying the connection weight when the end condition is satisfied;
second connection weight modification means for modifying the connection weight when evaluation by a user on the result of driving performed by the driving means is given as a reward by the user; and
second learning means for learning the second self-organization map based on the second parameter obtained when the end condition is satisfied. - View Dependent Claims (2, 3, 4)
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5. An information processing method comprising the steps of:
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based on a first parameter extracted from an observed value output by observation means that observes an external world and outputs the observed value, learning a first self-organization map stored in connection network storage means that stores a connection network which includes a first self-organization map and second self-organization map each including a plurality of nodes and which also includes connection weights indicating connection strengths of nodes between the first self-organization map and the second self-organization map;
determining a winner node by detecting a node having highest likelihood that the first parameter is observed at the node in the first self-organization map and determining the detected node as the winner node;
searching the second self-organization map for a node having highest connection strength with the winner node and employing the detected node as a generation node;
generating a second parameter from the generation node;
modifying the second parameter generated from the generation node;
determining whether an end condition is satisfied to end modification of the second parameter, the modification being performed in accordance with the winner node determined for a value which is observed by the observation means when driving means performs a driving operation in accordance with the second parameter;
modifying the connection weight when the end condition is satisfied;
modifying the connection weight when evaluation by a user on the result of driving performed by the driving means is given as a reward by the user; and
learning the second self-organization map based on the second parameter obtained when the end condition is satisfied.
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6. A program to be executed by a computer, the program comprising the steps of:
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based on a first parameter extracted from an observed value output by observation means that observes an external world and outputs the observed value, learning a first self-organization map stored in connection network storage means that stores a connection network which includes a first self-organization map and second self-organization map each including a plurality of nodes and which also includes connection weights indicating connection strengths of nodes between the first self-organization map and the second self-organization map;
determining a winner node by detecting a node having highest likelihood that the first parameter is observed at the node in the first self-organization map and determining the detected node as the winner node;
searching the second self-organization map for a node having highest connection strength with the winner node and employing the detected node as a generation node;
generating a second parameter from the generation node;
modifying the second parameter generated from the generation node;
determining whether an end condition is satisfied to end modification of the second parameter, the modification being performed in accordance with the winner node determined for a value which is observed by the observation means when driving means performs a driving operation in accordance with the second parameter;
modifying the connection weight when the end condition is satisfied;
modifying the connection weight when evaluation by a user on the result of driving performed by the driving means is given as a reward by the user; and
learning the second self-organization map based on the second parameter obtained when the end condition is satisfied.
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7. An information processing apparatus comprising:
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a connection network storage unit adapted to store a connection network which includes a first self-organization map and a second self-organization map each including a plurality of nodes and which also includes connection weights indicating connection strengths of nodes between the first self-organization map and the second self-organization map;
a first learning unit adapted to learn the first self-organization map, based on a first parameter extracted from an observed value output by an observation unit adapted to observe an external world and output the observed value;
a winner node determination unit adapted to detect a node having highest likelihood that the first parameter is observed at the node in the first self-organization map and determine the detected node as a winner node;
a searching unit adapted to search the second self-organization map for a node having highest connection strength with the winner node and employ the detected node as a generation node;
a parameter generation unit adapted to generate a second parameter from the generation node;
a modification unit adapted to modify the second parameter generated from the generation node;
a determination unit adapted to determine whether an end condition is satisfied to end modification of the second parameter, the modification being performed in accordance with the winner node determined for a value which is observed by the observation unit when a driving unit performs a driving operation in accordance with the second parameter;
a first connection weight modification unit adapted to modify the connection weight when the end condition is satisfied;
a second connection weight modification unit adapted to modify the connection weight when evaluation by a user on the result of driving performed by the driving unit is given as a reward by the user; and
a second learning unit adapted to learn the second self-organization map based on the second parameter obtained when the end condition is satisfied.
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Specification