In the context of automated reasoning and logic programming, the algorithm that inverts a complete resolution strategy is known as the "Inverse Resolution" algorithm. This algorithm is a counterpart to the well-known resolution principle and plays a significant role in the field of automated theorem proving and symbolic reasoning.

Here's an explanation of the Inverse Resolution algorithm:

1. Resolution Principle: Before delving into Inverse Resolution, it's essential to understand the resolution principle. Resolution is a fundamental technique in first-order logic and automated theorem proving. It operates on clauses, which are disjunctions of literals (atomic statements or their negations). The goal of resolution is to prove the unsatisfiability (contradiction) of a set of clauses by deriving the empty clause (a clause with no literals).

2. Inverse Resolution: Inverse Resolution, on the other hand, reverses the direction of resolution. Instead of trying to derive the empty clause, it aims to construct a clause that, when combined with the original set of clauses, results in a specific goal clause. In other words, it works backward from a desired conclusion to find a suitable premise.

3. Applications: Inverse Resolution finds applications in various fields, including automated reasoning, natural language processing, and expert systems. It is used to generate explanations, diagnose problems, and perform abduction (inference of plausible explanations for observed phenomena).

4. Implementation: Implementing Inverse Resolution involves finding a way to add a new clause, called the "Inverse Resolution Clause," to the existing set of clauses to achieve the desired goal. This process typically requires careful manipulation of clauses and literals to ensure logical consistency.

5. Search Strategies: Inverse Resolution often involves search strategies to explore different paths of inference backward from a goal to premises. Various heuristics and search algorithms may be employed to efficiently find a suitable set of clauses that, when combined, lead to the desired conclusion.

Inverse Resolution is a powerful technique for automated reasoning, especially when the goal is to explain or deduce conclusions from a given set of premises. It complements the forward-chaining resolution strategy and is an important tool in the arsenal of logic-based systems and knowledge representation in AI and computer science.