Scientific Programming / 2020 / Article / Tab 4

Research Article

Bayesian-Based Search Decision Framework and Search Strategy Analysis in Probabilistic Search

Table 4

Performance comparisons in three different scenarios.

Evaluation parametersScenario aScenario bScenario c

E[TTDs]myopic60.0361.6261.86
E[TTDc]myopic68.3269.3369.67
Pmyopic97.85%96.80%95.86%
E[TTDs]saccadic69.0471.6172.35
E[TTDc]saccadic413.36502.21603.33
Psaccadic97.88%96.89%96.02%
E[TTDs]improved saccadic40.2255.3260.14
E[TTDc]improved saccadic330.65405.44500.21
Pimproved saccadic98.10%97.85%97.35%

Scenario a: the search agent starts at the same location. Scenario b: the search agent starts from a local peak in a priori graph with multiple peaks. Scenario c: the search agent starts from the grid with the lowest confidence in the initial belief map.