Camelot Jr. recursive backtracking solver agent¶

Design · All designs
Evidence · 1 claim (1 for) · 1 study (1 design), q1 · 0 of 1 report an effect size · 1 claim rests on one study

Description¶

A game-playing agent for Camelot Jr. implemented as 'a recursive backtracking protocol' that searches the permutation space of the block inventory for arrangements satisfying two independent criteria: Static Stability and Path Connectivity. Mirroring a human player, it places blocks one after another, evaluates structural validity once the inventory is fully deployed, and then evaluates path connectivity. It also 'implements geometric pruning strategies to cut off impractical search branches that cannot connect the start and the end points with the remaining inventory'.

Design Implications¶

Context¶

Requirements¶

A limited block inventory and grid layout defining the challenge
Support-footprint validation before committing to each placement
Backtracking with state reversion when stability or path criteria fail

Constraints¶

Stability is checked only after all blocks are placed, since counterweights can stabilize an initially unstable arrangement

Target Learners¶

players of the Camelot Jr. puzzle game
children training spatial skills

Learning Goals¶

block placement under stability constraints
pathfinding from start to goal

Claims¶

Camelot Jr Solver Solves Arbitrary Configurations [+W]

Examples¶

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Key Sources¶

Abhishek Jaiswal, Zoe Falomir. (2026). A Qualitative Model for Reasoning about Path and Support. arXiv preprint. https://arxiv.org/abs/2609.20349

Page metadata

Field	Value
`type`	`design`
`id`	`camelot-jr-backtracking-solver-agent`
`title`	`Camelot Jr. recursive backtracking solver agent`
`description`	`A game-playing agent for Camelot Jr.`
`status`	`review`
`generated`	by `process:settle-candidates` on `2026-10-11`
`trust`	unverified — no one has confirmed this page's content
`sources`	1 — `abhishek-jaiswal-2026`

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