Machine that learns what it actually does
First Claim
1. A self-learning and self-organizing machine that operates in a sequence of sensing and action periods of predetermined duration, said machine comprising:
- a. a timing means to herald a beginning and an end of a sensing and action period within said sequence of said sensing and action periods, andb. at least one sensor means to measure a value of said sensor means at said beginning of said sensing and action period, andc. at least one actuator means to make an attempt to produce a selected value of said actuator means during said sensing and action period, andd. a feedback sensing means to measure an actual value of said actuator means after a predetermined delay from said attempt to produce said value of said actuator means, ande. a self-learning memory means to make a record of a confidence level of said actual value of said actuator means occurring with said value of said sensor means in each said sensing and action period, andf. said self-learning memory means to select said selected value of said actuator means, said selected value having a highest of said confidence level within said record, andg. an actuator brake means to restrain said actuator means except when said self-learning memory means makes said attempt to produce said selected value of said actuator means, wherebyh. said self-learning machine attempts to produce a highest historical probability of said actual value of said actuator means occurring with said value of said sensor means in said sensing and action period, said self-learning machine also being self-organizing.
0 Assignments
0 Petitions
Accused Products
Abstract
A self-learning machine 10 with one or more sensor(s) 110 and actuator(s) 135, and a plurality of memory cells 20 that select actions for the actuator(s) 135 to be carried out during specific sensing and action periods, the selection being determined by the stored values in the memory cells 20 and the conditions identified by its sensor(s) 110 in these sensing and action periods. The stored values are reduced in the selecting memory cells 20 when they select specific actions, and the stored values are increased in selected memory cells 20 according to what actions actually occur within these specific sensing and action periods.
-
Citations
6 Claims
-
1. A self-learning and self-organizing machine that operates in a sequence of sensing and action periods of predetermined duration, said machine comprising:
-
a. a timing means to herald a beginning and an end of a sensing and action period within said sequence of said sensing and action periods, and b. at least one sensor means to measure a value of said sensor means at said beginning of said sensing and action period, and c. at least one actuator means to make an attempt to produce a selected value of said actuator means during said sensing and action period, and d. a feedback sensing means to measure an actual value of said actuator means after a predetermined delay from said attempt to produce said value of said actuator means, and e. a self-learning memory means to make a record of a confidence level of said actual value of said actuator means occurring with said value of said sensor means in each said sensing and action period, and f. said self-learning memory means to select said selected value of said actuator means, said selected value having a highest of said confidence level within said record, and g. an actuator brake means to restrain said actuator means except when said self-learning memory means makes said attempt to produce said selected value of said actuator means, whereby h. said self-learning machine attempts to produce a highest historical probability of said actual value of said actuator means occurring with said value of said sensor means in said sensing and action period, said self-learning machine also being self-organizing. - View Dependent Claims (2, 3, 4, 5, 6)
-
Specification