Grammar-guided genetic programmingGrammar-guided genetic programming isGrammatical evolution a type of genetic programming that uses grammatical rules to constrain the search space of the solutions. There are different representations of grammar-guided genetic programmingGrammar-guided genetic programming, including grammatical evolutionGrammatical evolution, structured grammatical evolutionDynamically Structured Grammatical Evolution, and context-free grammar genetic programming. Each representation introduces distinctive characteristics that shape the evolutionary process. In this chapter, we propose a new representation that uses a tree structure with non-encoding nodesNon-encoding nodes for the individuals in the population; Tree-Based Grammatical EvolutionGrammatical evolution with non-encoding NodesNon-encoding nodes. This representation increases the size and complexity of the individuals while performing a more exhaustive exploration of the solution space. Each node of the tree will have a set of children nodes and an associated number; this number determines which of the children nodes are used in decoding the solution and which are non-encoding nodesNon-encoding nodes. Those nodes carry out a concomitant evolutionaryConcomitant evolution process that may manifest on the phenotype after eventual mutation or crossover events. We investigate the performance of our proposal with a set of well-known benchmarks. Experimental results analyze the differences and similarities with other methods that also use grammars to guide the solutions and indicate the utility of the tree-based grammatical evolutionGrammatical evolution with non-encoding nodesNon-encoding nodes.