Moreover, if such plan is not found, then a consistent solution executor for a given composition problem does not exist.
If PLAN I,G) returns state-action table SA, then Σ SA is a consistent solution executor for the respective composition problem.
By directly applying the planning algorithm to planning domain Σ CF and planning goal ρ, we obtain the plan that is a consistent solution executor for a composition problem of Ψ and ρ.
The composition engine accepts as input a context C represented by context properties p 1,p 2,…,p m, a set of fragments ({F}^ =left {f_{1}^, f_{2}^,ldots,f_{n}^right }) annotated over C (together C and F + form a contextaware system Ψ=〈F +,C〉) and composition requirements ρ expressed as a context formula over C. The output is an executor Σ E that is a consistent solution executor for Ψ and ρ.
Based on fundamental flow equations describing mass balance, energy conservation and momentum, a consistent solution is derived for natural ventilation by thermal buoyancy in a room with two openings and with uniform temperature.
This equation gives x = 2 γ 1 + γ Open image in new window for a consistent solution, and after replacing into Equation 7, we find x ≈ − 4.6 and γ ≈ − 0.7.
The routine for searching a consistent solution executor is presented in Fig. 10.
Once a planning problem is obtained, a consistent solution executor is derived by the algorithm for strong planning in asynchronous domain presented in [18].
It can perform the automatic interpretation of structure planes and extraction of geometric parameters, and provide an effective and consistent solution for drilling information acquisition and borehole camera image signal processing.
In the current study, we accepted the two-cluster solution as the most consistent solution for a population-based map of the FPC.
