Path
A path is an ordered sequence of connected elements representing a route through a graph, structure, or space.
Grokking AI Algorithms, Second Edition
A path is an ordered sequence of steps or transitions leading from an initial situation toward a goal.
- How it is used
- Frames search as choosing among sequences of moves that lead from an initial situation toward a goal.
- How deep it goes
- Defines paths through nodes and edges, then shows parent links reconstructing a maze route during breadth-first search.
- Examples
- Uses maze routes, a nine-node tree path, city routes, and parent pointers in a BFS implementation.
- What you can do after
- Apply parent links from breadth-first search to reconstruct a route from a discovered goal back to its start.
Read how Grokking AI Algorithms, Second Edition explains path →
How Computers Make Books
A path is an ordered sequence of graphical segments that defines a connected outline or shape.
- How it is used
- Uses paths to assemble Bézier segments into letter outlines and boundaries for filled shapes.
- How deep it goes
- Explains endpoint continuity, smooth joins, gaps, fill rules, self-crossings, and path reversal without formal path-data syntax.
- Examples
- Illustrates paths through an ampersand with three curve chains, an O with inner and outer boundaries, and a self-crossing outline.
- What you can do after
- Evaluate/understand how joining, smoothing, orienting, and filling paths changes a rendered letter shape.
Learn Haskell by Example
A path is an ordered sequence of connected elements linking one element or state to another.
- How it is used
- Uses paths to model and search chains of valid transitions between a starting element and a destination.
- How deep it goes
- Explains nodes, edges, direction, equal costs, and shortest-path goals, but stops before specifying a complete search implementation.
- Examples
- Demonstrates paths through cat-to-dog and find-to-solution word ladders, including both longer and shorter alternatives.
- What you can do after
- Apply path modeling to represent transitions and frame shortest-route tasks across word, navigation, database, and network problems.
Grokking Data Structures
A path is a sequence of connected nodes in a graph from one vertex to another.
- How it is used
- Uses paths to describe traversal, ancestry, height, cycles, and structural relationships in graphs, trees, and heaps.
- How deep it goes
- Defines connected edge sequences and derives tree and heap properties, but stops short of implementation or traversal algorithms.
- Examples
- Traces animal follower edges, root-to-leaf tree routes such as 0→2→6→3, and sorted root-to-leaf heap paths.
- What you can do after
- Evaluate paths, cycles, ancestry, and tree or heap height in small graph-based examples.
Related concepts
- cycleincludes · A cycle is a recurring sequence of connected elements or events that returns to an earlier point, forming a loop.
- backdoor pathincludes · A backdoor path is a path between a putative cause and an outcome that begins with an arrow into the cause and can create a noncausal association.
- endpointpart of · An endpoint is a network-accessible address or interface through which a system or service receives requests, provides responses, or exposes a specific operation or resource.
- chainincludes · A chain is a three-node directed path in which the arrows point consecutively in the same direction, as in X→Y→Z or X←Y←Z.
- forkincludes · A fork is a three-node causal structure in which one central node is a common cause of two other nodes, as in X←Z→Y.
- causal pathincludes · A directed sequence of factors or variables through which changes can be transmitted from a cause to an outcome.
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