The positive and negative example regions of different concepts. The horizontal dimension corresponds to the change in situations over time. A, B, and P are the accepted annotation where P is the context annotation of A and B. + A E and − A E mark the positive and negative example regions of the annotation A. To create positive (negative) examples of the concept con of an operator op A , first an annotation A with the operator instance op A (x 0 ) and context c 0 is randomly selected from the annotation hierarchy. Next, a situation s 0 in c 0 is randomly selected from a set of situations + A E ( − A E ) called the positive (negative) example regions to obtain a positive (negative) example con(s 0 , c 0 , op A (x 0 )). Each decision concept has a corresponding function that maps an annotation A to negative and positive example regions for that decision concept. Figure 15 depicts this mapping for different decision concept kinds, such that the example regions + A E and − A E are calculated given an annotation A with the operator op A. The horizontal dimension represents temporally consecutive situations in the behavior trace and the boxes represent the accepted annotations. P is the context annotation of A, and B is a randomly selected accepted annotation in the same context with A. The operator op B of the annotation B may have the same operator name with op A , but it should have a different parameter instantiation. For example, for selectioncondition(op A ), + A E is selected from a set of situations right around the initial situation of

Contexts in source publication

Context 1

... decision concept of an operator op is a mapping from the internal state of the agent and the perceived external state of the environment to a "decision suggestion" about the activity of op. Figure 15 depicts four decision concepts, selection-condition (when the operator should be selected if it is not currently selected), overriding-selection- condition (when the operator should be selected even if another operator is selected), maintenance-condition (what must be true for the operator to be continued during its application), and termination-condition (when the operator has completed and should be terminated). ...

Context 2

... door d 2 could also be leading to the same target), and once it is activated, no other alternative operator is considered until its termination. At the situation where the execution condition of get- item(i 1 ) does not hold (i.e. the termination condition is just satisfied when the agent has grabbed i 1 ), all suboperators below this get-item instantiation are automatically retracted due to the first assumption in Definition 3. On the other hand, the learning system is biased with the first assumption by generating examples of a decision concept only at regions where the parent operator is active ( Figure 15). The second assumption is also used in generating the examples, where an operator op A is treated as undesired at a situation where another operator op B is selected (Figure 15.b). ...

Context 3

... the situation where the execution condition of get- item(i 1 ) does not hold (i.e. the termination condition is just satisfied when the agent has grabbed i 1 ), all suboperators below this get-item instantiation are automatically retracted due to the first assumption in Definition 3. On the other hand, the learning system is biased with the first assumption by generating examples of a decision concept only at regions where the parent operator is active ( Figure 15). The second assumption is also used in generating the examples, where an operator op A is treated as undesired at a situation where another operator op B is selected (Figure 15.b). ...

Context 4

... negative example regions in Figure 15.b, c, d implicitly assume that the selection of an operator op A is undesirable when another operator op B is selected. ...

Context 5

... negative examples are created by using the same situation s 0 , context c 0 , and operator name go-to-door, whereas the argument of go-to-door is selected from a set of arguments that were used in instantiations of that operator at different annotations on the behavior trace. To differentiate between these two heuristic mechanisms that generate negative examples from a correct trace, we will call the heuristic negative examples as generated in Figure 15.b, c, d situation heuristic negative examples, whereas we call the negative examples as generated in Figure 17 parameter heuristic negative examples. ...

Context 6

... positive examples of the selection condition concept would be obtained from accepted annotations generated in the first mode of our framework (Figure 15), whereas the negative examples would be come from rejected annotations (Figure 16) that are generated in the second mode of our framework. ...