Research programs exploring heuristic discovery: which series of AI systems by Pat Langley investigated how heuristics can drive scientific law discovery from data?

Introduction / Context:
One line of AI research investigated how scientific laws might be induced from empirical data using heuristic search and representation choices. Such systems illuminated how concept formation, measurement selection, and search biases can uncover regularities that resemble scientific laws.

Given Data / Assumptions:

• The question asks for the series name associated with Pat Langley.
• The goal of the series was to explore the role of heuristics in scientific discovery.
• Other options are distractors without direct relevance.

Concept / Approach:
Pat Langley and collaborators developed the BACON series, which modeled the discovery of quantitative laws (e.g., proportionalities) from data. The systems used heuristic strategies to guide search through hypothesis spaces, reflecting how practical scientific reasoning often proceeds.

Step-by-Step Solution:

Verification / Alternative check:
AI histories and machine discovery literature consistently associate Langley with BACON as a canonical example of discovery systems.

Why Other Options Are Wrong:

• MIT: an institution, not the system series.
• RAMD/DU: do not name Langley’s discovery systems.
• None: incorrect because BACON is correct.

Common Pitfalls:
Confusing SHRDLU/ELIZA (NLP) with discovery systems; overlooking that BACON addresses scientific induction tasks.

Final Answer:
BACON