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[HE SUBSET OF DIRECT FEATURES USED FOR PREDICTING PLAYERS’ REPORTED EXPERIENCE AND THE CORRESPONDING MODELS’ TOPOLOGIES AND PERFORMANCE AS PRESENTED IN [19]

Table 2 [HE SUBSET OF DIRECT FEATURES USED FOR PREDICTING PLAYERS’ REPORTED EXPERIENCE AND THE CORRESPONDING MODELS’ TOPOLOGIES AND PERFORMANCE AS PRESENTED IN [19]

Related Figures (5)

Fig. 1. Snapshot from Infinite Mario Bros, showing Mario standing on horizontally placed blocks surrounded by different types of enemies.
Fig. 1. Snapshot from Infinite Mario Bros, showing Mario standing on horizontally placed blocks surrounded by different types of enemies.
Fig. 2. Enemies placement using different probabilities: high probability is given to placement around horizontal boxes, Pp (a), around gaps, Pg (b), and to random placement, P;. (c).
Fig. 2. Enemies placement using different probabilities: high probability is given to placement around horizontal boxes, Pp (a), around gaps, Pg (b), and to random placement, P;. (c).
Fig. 4. Snapshot from a level and the corresponding platform structure sequence representation, P (a), and enemies and items sequence represen- tation, I (b).
Fig. 4. Snapshot from a level and the corresponding platform structure sequence representation, P (a), and enemies and items sequence represen- tation, I (b).
ml Sad ON, BEST MLP TOPOLOGIES AND CORRESPONDING PERFORMANCE ON DIRECT AND SEQUENTIAL FEATURES. THE PERFORMANCE OF MLP MODELS BUILT ON THE SUBSET OF SELECTED FEATURES, M LP; IS COMPARED AGAINST THE MODELS BUILT ON SELECTED AND FORCED CONTROLLABLE FEATURES, ML P.. THE TOPOLOGIES ARE PRESENTED IN THE FORM: NUMBER OF INPUTS-NUMBER OF NEURONS IN THE FIRST HIDDEN LAYER-NUMBER OF NEURONS IN THE SECOND HIDDEN LAYER. these two types together, simple jumping actions, {}, can be explained by changes in platform height and placement of items; moving right followed by jumping and standing still patterns ((m, ff, 5) and (»)({}",S)) mostly relates to ‘ . : oo the behaviour of overcoming enemies @ a) , © ); the more complex navigation patterns that has been selected, such as (R™,R™,R”*) that defines the behaviour of pressing a combination of buttons at the same time within a very small window time, suggest the existence of a gap that requires speeding up followed by jumping while the moving right and the speed button are still pressed ((™%,7, )). Note that the two patterns ((m, {}, S) and (»)({}",S)) can also be the result of overcoming a gap, which in that case reflect a beginner player playing style. On the contrary the pattern
ml Sad ON, BEST MLP TOPOLOGIES AND CORRESPONDING PERFORMANCE ON DIRECT AND SEQUENTIAL FEATURES. THE PERFORMANCE OF MLP MODELS BUILT ON THE SUBSET OF SELECTED FEATURES, M LP; IS COMPARED AGAINST THE MODELS BUILT ON SELECTED AND FORCED CONTROLLABLE FEATURES, ML P.. THE TOPOLOGIES ARE PRESENTED IN THE FORM: NUMBER OF INPUTS-NUMBER OF NEURONS IN THE FIRST HIDDEN LAYER-NUMBER OF NEURONS IN THE SECOND HIDDEN LAYER. these two types together, simple jumping actions, {}, can be explained by changes in platform height and placement of items; moving right followed by jumping and standing still patterns ((m, ff, 5) and (»)({}",S)) mostly relates to ‘ . : oo the behaviour of overcoming enemies @ a) , © ); the more complex navigation patterns that has been selected, such as (R™,R™,R”*) that defines the behaviour of pressing a combination of buttons at the same time within a very small window time, suggest the existence of a gap that requires speeding up followed by jumping while the moving right and the speed button are still pressed ((™%,7, )). Note that the two patterns ((m, {}, S) and (»)({}",S)) can also be the result of overcoming a gap, which in that case reflect a beginner player playing style. On the contrary the pattern
THE PERFORMANCE OF THE MODELS OF [19] ON THE NEW DATASET (Pota/new) COMPARED TO THE PERFORMANCE OF THE NEW MODELS ON THE DATASET OF [19] (Prew/ola)
THE PERFORMANCE OF THE MODELS OF [19] ON THE NEW DATASET (Pota/new) COMPARED TO THE PERFORMANCE OF THE NEW MODELS ON THE DATASET OF [19] (Prew/ola)
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